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Introduction Thyroid dysfunction is the most frequent endocrine immune related adverse event (irAE) in non-small cell lung cancer (NSCLC), typically arising 3–6 months into immune checkpoint inhibitor (ICI) therapy, but arising after ICI cessation, in some cases. Due to limited post-treatment adverse event reporting requirements on ICI trials, the incidence of ICI-induced thyroid dysfunction arising after therapy is unclear. We investigated ICI-induced thyroid dysfunction in a cohort of 294 NSCLC patients, with a specific focus on the post-treatment setting. Methods Retrospective analysis of ICI-induced thyroid dysfunction (clinically acted upon or laboratory only) was performed in 294 UCLA NSCLC patients treated 2012–2018. Clinically acted upon thyroid dysfunction was defined as thyroid diagnosis documentation and/or thyroid medication administration. Laboratory only dysfunction was defined as abnormal thyroid labs in the absence of clinical action. Timing of thyroid dysfunction relative to ICI treatment and thyroid monitoring patterns were also assessed. Results 82% (241/294) of ICI treated NSCLC patients had thyroid labs during treatment. Of these 241 patients, 13% (31/241) had clinically acted upon thyroid dysfunction prior to, 8% (18/241) during, and 4% (9/241) after ICI. Most patients, 66% (159/241), did not have thyroid labs after ICI, but in the 53 patients with labs and no prior clinical dysfunction, 17% (9/53) developed clinical dysfunction after ICI. In these 9 patients, median time from ICI initiation to dysfunction was 253 days. Two patients with post-treatment laboratory only dysfunction were observed. Conclusions ICI-induced thyroid dysfunction arising post-treatment appears more common than previously appreciated, warranting additional evaluation.

Identifying patients who respond to immune checkpoint blockade (ICB) is a significant challenge in oncology. While PD-L1 expression by immunohistochemistry (IHC) is the current diagnostic gold standard for patient selection, it nevertheless does not capture all patients who may respond to ICB. Recent gene expression studies in high-grade serous ovarian carcinoma have defined an immunoreactive molecular subtype that has a measurable difference in patient survival compared with non-immunoreactive subtypes, but no studies have yet demonstrated its impact on predicting response to ICB. As a step toward establishing the predictive value of gene expression classifiers in ICB, we assessed the relationship between PD-L1 IHC and molecular subtypes of ovarian epithelial cancer. This was done by analyzing a total of 93 tissue specimens from patients with stage III and IV disease, and comparing PD-L1 IHC with gene expression by Agilent microarrays using TCGA-defined subtypes. We showed that ovarian tumors with elevated IHC PD-L1 expression are most strongly associated with immunoreactive subtype as compared with other molecular subtypes, reaching statistical significance against differentiated (Dunn’s test, 33.39, p = 0.0003) and mesenchymal (39.63, p

The emergence of immune checkpoint blockade therapies over the last decade has transformed cancer treatment in a wide range of tumor types. Unprecedented and durable clinical responses in difficult-to-treat cancer histologies have been observed. However, despite these promising long-term responses, the majority of patients fail to respond to immune checkpoint blockade, demonstrating primary resistance. Additionally, many of those who initially respond to treatment eventually experience relapse secondary to acquired resistance. Both primary and acquired resistance are a result of complex and constantly evolving interactions between cancer cells and the immune system. Many mechanisms of resistance have been characterized to date, and more continue to be uncovered. By elucidating and targeting mechanisms of resistance, treatments can be tailored to improve clinical outcomes. This review will discuss the landscape of immune checkpoint blockade response data, different resistance mechanisms, and potential therapeutic strategies to overcome resistance.

Human leukocyte antigen (HLA)-B has been recognized as a major determinant of discrepancies in disease outcomes, and recent evidence indicates a role in immune checkpoint blockade (ICB) efficacy. The B44 supertype, which features an electropositive binding pocket that preferentially displays peptides with negatively charged amino acid anchors, is associated with improved survival in ICB-treated melanoma. Yet this effect was not seen in ICB-treated non-small-cell lung cancer (NSCLC). Here we show that mutations leading to glutamic acid substitutions occur more often in melanoma than NSCLC based on mutational landscape. We additionally show stratifying B44 based on the presence of somatic mutations that lead to negatively charged glutamic acid anchors identifies patients with NSCLC with an ICB benefit similar to that seen in melanoma. We anticipate these findings could improve assessment of HLA-related outcomes and prediction of ICB benefit in those with B44, representing approximately half of the world’s population. Garon and colleagues demonstrate that the association of HLA supertype B44 with response to immune checkpoint blockade in melanoma but not NSCLC is related to differential mutational features that influence HLA binding of neoepitopes.

Purpose of review Immune checkpoint blockade (ICB) is a promising area of cancer therapeutic research. Therapies targeting the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) mechanism of tumor immune evasion have resulted in durable responses in many difficult-to-treat tumor types. While these inhibitors are being actively investigated in clinical trials for ovarian cancer, most patients fail to respond to initial treatment with immune therapy. This review focuses on biomarkers for predicting response to treatment, and discusses clinical trials using ICB for recurrent ovarian cancer. Recent findings While PD-L1 detection by immunohistochemistry (IHC) is approved as a companion or complementary diagnostic in some cancers, there are many limitations with its use as a predictive marker. Recent research has explored biomarkers beyond PD-L1 that assess for somatic mutations, immune cell infiltrate, and gene signatures. Summary With improved understanding of the tumor microenvironment and genomic classifications of ovarian tumors, new diagnostics and biomarkers that supplement conventional IHC may help predict response to therapy.

5536 Background: Immune checkpoint blockade (ICB) is being explored as a treatment option in ovarian cancer, but objective response rates for single agent ICB are modest at around 10-15%. Validated biomarkers are needed to predict which patients will respond to ICB. BRCA mutations and homologous recombination deficiency (HRD) status are the only validated integral biomarkers in ovarian cancer. HRD tumors exhibit defective DNA repair mechanisms that promote increased mutational burden, which we postulate may correlate with higher neoantigen load and increased expression of targetable immune checkpoints. Methods: The Cancer Genome Atlas (TCGA) ovarian cancer dataset was evaluated and previously published, well annotated samples were obtained for HRD status. HLA type was determined with OptiType. Nonsynonymous mutations were annotated with Ensembl VEP. pVAC-Seq using NetMHCpan algorithm predicted neoepitopes 9 amino acids in length for MHC class I, reporting only those with a predicted IC50 less than 500 nM. Immune checkpoint gene expression counts were normalized with TCGAbiolinks. Correlation between HRD status and neoantigen load was assessed by Wilcoxon test. After log2 transformation, Wilcoxon tests evaluated for association between HRD status and expression of immune checkpoints. The relationship between HRD status and PD-L1 protein abundance with reverse phase protein array was measured. Results: Data from 154 HRD positive and 198 HRD negative tumors were analyzed. HRD positive status correlated with higher neoantigen load (p = 0.038) and increased expression of the immune checkpoints CTLA4 (p = 0.024), TIGIT (p = 0.027), and PVR (p = 0.002), but not PD-L1 (p = 0.238), LAG3 (p = 0.583), HVEM (p = 0.805), GAL9 (p = 0.750), NECTIN2 (p = 0.874), VSIG3 (p = 0.438), PSGL1 (p = 0.205) or VISTA (p = 0.531). TIM3 (p = 0.064) and B7H3 (p = 0.052) both demonstrated a trend towards increased expression in HRD tumors. Interestingly, HRD status showed a negative association with PVRIG (p = 0.028). There was no association between PD-L1 protein abundance and HRD status. Conclusions: HRD positive ovarian tumors demonstrate higher neoantigen load than HRD negative tumors, as well as increased expression of certain immune checkpoints. This supports the hypothesis that increased neoantigen load leads to compensatory induction of immune checkpoints, and suggests that HRD status may predict response to ICB, particularly to drugs that target CTLA4, TIGIT, PVR, TIM3 and B7H4.