Precision immunotherapy requires understanding of both tumor microenvironment (the tumor) and macroenvironment (the host, i.e., the patient). A comprehensive presentation was delivered by Elizabeth Jaffee (Johns Hopkins), Tim Chan (Memorial Sloan-Kettering), Drew Pardoll (Johns Hopkins), and Siwen Hu-Lieskovan (UCLA). Immunogenomics is a rapid expanding area that allows researchers to interrogate and understand how changes of the cancer genome affect immunity or treatment responsiveness. For example, understanding tumor mutation burden (TMB), immunoediting score etc. will enable researchers and physicians to guide ICI therapy [
35,
36]. Understanding TCR repertoire, neoantigen epitopes and HLA haplotypes will facilitate effort in neoantigen vaccine development and cell therapy. Jaffee discussed their meta-analysis results of patients on anti-PD-1/PD-L1 agents whose exome sequencing information were available [
37]. They found a strong relationship between the tumor mutational burden and the activity of anti–PD-1 therapies across multiple cancer types. Their analysis allowed them to calculate objective response rate (ORR) with a linear correlation formula: ORR = 10.8 × log
e(
X) − 0.7, where “
X” is the number of coding somatic mutations per megabase of DNA. Validation of this finding with future prospective trials shall be helpful to guide the selection of patients for ICIs. Catherine Wu and her colleagues have identified a subcluster of MAGE-A cancer-germline antigens, located within a narrow 75 kb region of chromosome Xq28, that predicts resistance uniquely to blockade of CTLA4, but not PD-1 [
38]. Tim Chan discussed the exciting study from his group that highlighted the importance of mutation of specific genes correlating to ICI responsiveness. They reported that somatic mutations in SERPINB3 and SERPINB4 are associated with survival after anti-CTLA4 immunotherapy in two independent cohorts of patients with melanoma (
n = 174), although the underlying mechanism is unclear [
39]. Furthermore, Tim Chan’s group determined the HLA class I genotype of 1535 advanced cancer patients treated with ICIs. They found that maximal heterozygosity at HLA class loci correlated with improved overall survival compared with patients who were homozygous for at least one HLA locus. Curiously, in two independent melanoma cohorts, patients with the HLA-B44 had extended survival, whereas the HLA-B62 supertype (including HLA-B*15:01) or somatic loss of heterozygosity at HLA class I was associated with poor outcome [
40]. Hu-Lieskovan discussed several lines of work in UCLA, including a remarkable 70% clinical response of patients with desmoplastic melanoma to PD-1 blockers, which correlated with high tumor mutation burden and frequent NF1 mutations in this unique subset of melanoma patients [
41]. PD-1 blocker-based therapy ultimately depends on CD8
+ T cells and IFNγ for cancer eradication. Not surprisingly, loss of function mutations of MHC class I (e.g., loss of β2m) and key IFNγ signaling molecules JAK1/2 in the cancer are associated with intrinsic resistance to anti-PD-1 therapy [
42,
43]. Perhaps, a more striking example of impact of cancer genomics on ICI treatment is the status of microsatellite instability-high (MSI-H) or DNA mismatch repair deficiency (dMMR) in the tumors [
44‐
47]. About ~ 50% patients with advanced cancers and the defect in the mismatch repair pathway will derive clinical benefit in response to nivolumab or pembrolizumab. Genomics study of cancer can also shed light on the mechanism of immune evasion. For example, a multi-omic analysis of 1211 colorectal cancer primary tumors reveals that it should be possible to better monitor resistance in the 15% of cases that respond to ICI therapy and also to use WNT signaling inhibitors to reverse immune exclusion in the 85% of cases that currently do not [
48]. Genomic and immunologic studies have also uncovered specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers [
49]. The oncogenic pathways [
50], such as PTEN loss [
51,
52], and activation of the WNT/β-catenin signaling pathway [
53] have been shown to lead to poor T cell infiltration and function in the tumor microenvironment.
In the field of personal neoantigen vaccines [
54], there have been several high profile proof-of-principle studies. Ott et al. demonstrated the feasibility, safety, and immunogenicity of a neoantigen vaccine platform (up to 20 personized HLA-A/B-restricted peptides plus poly-ICLC as adjuvant) that targets advanced melanoma [
55]. Evidence for T cells discriminating mutated from wild-type antigens was shown for some patients. Another group tested RNA-based poly-neo-epitope approach for patients with melanoma [
56]. They found evidence suggesting that patients developed T cell responses against multiple vaccine neo-epitopes and increased T cell infiltration and neo-epitope-specific killing of autologous tumor cells in post-vaccination resected metastases. Although the sample size is too low to conclude the clinical utility for all of these studies, the neoantigen-based approach may prove to be useful in the adjuvant setting, particularly in combination with ICIs. Pardoll discussed their allele-integrated deep learning framework for improving class I and class II HLA-binding predictions, which may be useful for future neoantigen vaccine effort and also the expansion of tumor antigen-specific T cells [
57]. Jaffee also discussed the Hopkins experience on the combination of neoantigen vaccine and ICIs and other IO agents such as CD40 agonist, CXCR4 inhibitor, and agents that target CD47, CSF1R, IDO, TGF-β, A2A, etc. But these studies are mostly at the preclinical stage. Undoubtedly, effective cancer immunotherapy depends on robust priming of tumor-specific T cells, enabling T cells to infiltrate the tumors and ensuring effective mechanism to prevent T cell dysfunction due to hostile tumor microenvironment.