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3. Combination immunotherapy including OncoVEXmGMCSF creates a favorable tumor immune micro-environment in transgenic BRAF murine melanoma

4. Introducing cancer convergence

5. First-in-Human Phase I Trial of TPST-1120, an inhibitor of PPARα, as Monotherapy or in Combination with Nivolumab, in Patients with Advanced Solid Tumors

6. Differential histone acetylation and super-enhancer regulation underlie melanoma cell dedifferentiation

7. Immunotherapy Efficacy in Advanced Hepatocellular Carcinoma in a Diverse and Underserved Population in the United States

8. Evaluating the efficacy of combination and single-agent immunotherapies in real-world patterns of disease progression and survival of metastatic melanoma patients

9. 750 A phase 1 trial of CUE-102, a novel WT1-pHLA-IL2-Fc fusion protein in HLA-A*0201 positive patients with WT1-positive recurrent/metastatic cancers

12. Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma

17. Future perspectives in melanoma research: meeting report from the "Melanoma Bridge", Napoli, December 5th-8th 2013

20. Immune and genomic correlates of response to anti-PD-1 immunotherapy in glioblastoma

21. Supplemental Figure S3 from Requirement for Innate Immunity and CD90+ NK1.1− Lymphocytes to Treat Established Melanoma with Chemo-Immunotherapy

22. Supplemental Methods from Requirement for Innate Immunity and CD90+ NK1.1− Lymphocytes to Treat Established Melanoma with Chemo-Immunotherapy

23. Supplemental Table S1-4 and Supplemental Figure S1-S7 from Quantitative Analysis of Immune Infiltrates in Primary Melanoma

24. Supplemental Figure Legends from Requirement for Innate Immunity and CD90+ NK1.1− Lymphocytes to Treat Established Melanoma with Chemo-Immunotherapy

25. Data from Requirement for Innate Immunity and CD90+ NK1.1− Lymphocytes to Treat Established Melanoma with Chemo-Immunotherapy

26. Supplementary Table S1 from Quantitative Analysis of Immune Infiltrates in Primary Melanoma

27. SupplementaryTable S4 from Quantitative Analysis of Immune Infiltrates in Primary Melanoma

28. Data from Quantitative Analysis of Immune Infiltrates in Primary Melanoma

34. Supplemental Table ST2 from Linking Transcriptomic and Imaging Data Defines Features of a Favorable Tumor Immune Microenvironment and Identifies a Combination Biomarker for Primary Melanoma

35. Supplementary Data from Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death

36. Supplemental Figure S3 from Linking Transcriptomic and Imaging Data Defines Features of a Favorable Tumor Immune Microenvironment and Identifies a Combination Biomarker for Primary Melanoma

37. Data from Validation of Melanoma Immune Profile (MIP), a Prognostic Immune Gene Prediction Score for Stage II–III Melanoma

38. Figure S3 from Therapeutic Immune Modulation against Solid Cancers with Intratumoral Poly-ICLC: A Pilot Trial

39. Supplemental Figure Legends from Linking Transcriptomic and Imaging Data Defines Features of a Favorable Tumor Immune Microenvironment and Identifies a Combination Biomarker for Primary Melanoma

40. Table S2 from Therapeutic Immune Modulation against Solid Cancers with Intratumoral Poly-ICLC: A Pilot Trial

42. Figure S1 from Validation of Melanoma Immune Profile (MIP), a Prognostic Immune Gene Prediction Score for Stage II–III Melanoma

43. Table S1 from Validation of Melanoma Immune Profile (MIP), a Prognostic Immune Gene Prediction Score for Stage II–III Melanoma

44. Data from Linking Transcriptomic and Imaging Data Defines Features of a Favorable Tumor Immune Microenvironment and Identifies a Combination Biomarker for Primary Melanoma

46. Supplementary Figure Legends from Validation of Melanoma Immune Profile (MIP), a Prognostic Immune Gene Prediction Score for Stage II–III Melanoma

50. Using tumor growth rate to inform treatment efficacy in pancreatic adenocarcinoma: From the metastatic to the neoadjuvant setting.

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