Genetics Helps to Find Synergy for Immune Checkpoint and Targeted Combination Therapies

Starting from 2011, seven immune checkpoint inhibitors (ICI) have been approved by the U.S. FDA for different cancer indications. Most ICIs are mAbs that block the interaction between PD-1, the receptor expressed by activated T cells and its ligand, PD-L1, expressed by tumor cells. Blocking this interaction disrupts coinhibitory signaling and activates the immune system, allowing efficient tumor elimination by cytotoxic CD8⁺ T cells. The development of ICIs revolutionized cancer treatment. However, despite many success stories, ICI treatment is effective only for a small subset of patients. With 44% of all U.S. cancer patients considered to be eligible for some type of FDA-approved ICI, the overall response rates are low, only 13% (1). Significant efforts are now devoted to exploring the molecular mechanisms of treatment resistance and to identifying biomarkers that can predict response to ICIs. Combinations of ICIs targeting independent immunoregulatory pathways, such as CTLA-4 and PD-1/PD-L1 can improve response rates but also increase the risk of adverse effects.

Conventional therapies, that include radiation, chemotherapy, and molecular targeted therapies, also appeared to have systemic immunomodulatory effects. Although not specific, these effects result in increasing influx of tumor-infiltrating lymphocytes (TIL) and immunologically warming up the “cold” tumors enough to awake antitumor immunity and increase the response to ICIs. Hence, multiple combinations of ICIs and conventional therapies are now being tested for synergistic antitumor effects (2). In contrast to growing but still limited ICIs options, the options for conventional therapies are quite numerous. For example, years of laboratory and clinical investigations identified various molecular targeted therapies directed against well-established alterations in genes and pathways. Some examples of molecular targeted therapies developed for specific genetic alterations include inhibitors of BCR-ABL fusion in chronic myeloid leukemia and blockers of EGFR in lung cancer or FGFR3 in bladder cancer. The identification of the best molecular target therapies based on information about genetic alterations in tumors of different types is the concept of the NCI-MATCH Trial (Molecular Analysis for Therapy Choice), a pilot for precision cancer therapy approach.

Notably, in addition to serving as biomarkers and drug targets, genetic alterations also affect the immunologic environment of the tumors, which is important for both immune surveillance and treatment response. Thus, knowledge of genetic alterations provides an opportunity to optimize treatment responses by selecting patient populations for specific immune-based and -targeted therapies and their combinations. In the last several years, large-scale tumor sequencing, including efforts of The Cancer Genome Atlas (TCGA) identified thousands of somatic alterations (point mutations, structural alterations, etc.) in different tumor types. Thus, many more molecular targeted therapies are likely to be developed on the basis of somatic alterations identified by TCGA, and some of these drugs could be good candidates for synergistic combination therapies. This information is already contributing to a better understanding of molecular cancer mechanisms and supporting improved clinical decision making. For example, in addition to testing specific cancer mutations, clinical testing of the total tumor mutation burden (TMB) helps identify patients who are likely to benefit from treatment with ICIs (3). High TMB tumors are considered immunologically “hot” because they generate more neoantigens that are recognized by TILs attracted to tumors at high rates, especially after stimulation by ICIs.

One of the most commonly mutated genes cataloged by TCGA is ARID1A, with inactivating mutations detected in 26 of 32 tumor types tested. Uterine corpus endometrial carcinoma (UCEC) has the highest rates of ARID1A-mutated tumors (44% in TCGA). The rates are also high in some subsets of ovarian cancer, such as 46% in ovarian clear-cell carcinoma (OCCC) and 30% in endometrioid carcinoma, but low or absent in serous ovarian carcinoma (4). Although OCCC is treated with platinum-based chemotherapies, the responses are poor and short-lived. On the basis of a reported 15% response rate in the first anti-PD-1 clinical trial for ovarian cancer (5), there is a significant need for improvement in the treatment of this highly fatal cancer.

Histone deacetylase inhibitors (HDACI) are a unique class of targeted therapies. Rather than targeting specific mutations, HDACIs affect histone acetylation, a post-translational modification marking active chromatin. It appeared that ACY1215, an inhibitor of histone deacetylase 6 (HDAC6), specifically promotes apoptosis in ARID1A-mutated OCCC (6). Independently, the presence of ARID1A mutations was identified as a biomarker for sensitivity to pan-HDACIs in bladder tumors in two separate trials (7). To overcome significant resistance, HDACIs are often administered in combinations with other therapies (8). ARID1A encodes BAF250a, a subunit of the SWI/SNF complex that controls chromatin remodeling and access of regulatory proteins to DNA. By epigenetically opening/closing DNA for interactions with transcriptional activators and repressors, the SWI/SNF complex regulates global expression profiles. The unexpected link between the ARID1A mutations and response to HDACIs was explored in vitro and in vivo. Wild-type ARID1A was found to transcriptionally repress HDCA6 and prevent it from deacetylating the Lys120 residue (p53K120Ac), which is necessary for the proapoptotic activity of p53. Thus, blocking of HDAC6 compensated for mutated ARID1A and restored apoptotic elimination of cancer cells.

Another important piece of the puzzle was contributed by the search for ARID1A-interacting proteins (9). Specifically, ARID1A was found to be involved in regulating DNA damage repair during replication by recruiting a mismatch repair (MMR) protein MSH2 to chromatin. Thus, ARID1A-mutated tumors would be expected to have decreased DNA repair potential manifested by increased mutation rates. Accordingly, these tumors were found to have a high TMB with particularly high loads of C>T mutations, associated with MMR deficiency. The more active immune profiles of these tumors may explain significantly longer overall and progression-free survival of patients with UCEC (TCGA) carrying ARID1A mutations compared with patients with wild-type ARID1A. ARID1A-mutated tumors also showed upregulation of PD-1 and CD8⁺ expression, indicating the presence of infiltrating cytotoxic CD8⁺ T lymphocytes, both in mouse models and human OCCC tumors. The immunoregulatory activity of ARID1A appears to be independent of its chromatin remodeler function.

In this issue of Cancer Research, Fukumoto and colleagues (10) further expanded the work of several laboratories, including their own, on ARID1A-mutated OCCC. First, they explored the mechanism of regulation of PD-L1 expression by ARID1A in OCCC cell lines and an OCCC mouse model. They showed that ARID1A directly binds the promoter of CD274 gene (encoding PD-L1) and represses its transcription both in human and mouse cells. Next, based on molecular mechanisms of individual therapies, and the knowledge that ARIDA1-inactivated tumors are high TMB tumors with increased rates of TILs, they hypothesized that the response rates should be improved by the combination of these drugs. Indeed, based on a combination of HDAC6 inhibitor and anti-PD-L1 treatment, they demonstrated the CD8⁺ T-cell–dependent restoration of antitumor immunity, reduced tumor burden, and improved survival of mice with ARID1A-inactivated tumors. On the basis of these results, the authors suggested that a combination of the checkpoint and HDAC inhibitors should be tested in patients with OCCC with inactivating ARID1A mutations. These trials should address the benefits, side effects, and response durability of this combination therapy.

A notably high frequency of ARID1A mutations is observed in gynecologic cancers of endometrioid origin—OCCC (46%) and UCEC (44%). These mutations are also found in endometriosis, a common noncancerous gynecologic condition affecting up to 10% of reproductive-aged women. Although only a small proportion of endometriosis cases progress to cancer, it is possible that ARID1A mutations drive these transformations. Perhaps, early mutation detection and mutation-specific therapeutic measures could be taken to prevent the development of these endometrioid-type cancers, with inactivating ARID1A mutations as a common denominator.

TCGA identified thousands of somatic mutations, and many of them are highly recurrent and enriched in specific tumor types. Thus, there could be endless combinations of drugs targeting the relevant pathways. The logistical aspects of devising these drug combinations and considering their additive and synergistic effects are far from trivial. What would be the next drug combination and how would it be discovered? Would these candidates come from systematic high-throughput screening of multiple drug combinations? Screenings for drug effects in organoids would be more biologically relevant than in cell lines, but such experiments would still be in vitro. In vivo studies in mouse and other models must be developed to test the efficacy and safety of these drug combinations, which eventually need to be tested in human clinical trials. The example provided by Fukumoto and colleagues (10) demonstrates the value of detailed understanding of biological mechanisms of specific tumor mutations for selection of cancer therapies and their combinations and encourages similar analyses based on other common genetic alterations. This approach can include relevant germline genetic variations that define tumors with distinct functional features, such as variants in BRCA1, BRCA2, and TP53 genes, and those associated with Lynch syndrome, to name a few.

No potential conflicts of interest were disclosed.

This work was supported by the Intramural Research Program of the NIH, NCI, Division of Cancer Epidemiology and Genetics.