Immune checkpoint inhibitors have changed the way certain cancers are treated, but more can be done to optimize treatment and improve patient responses.
While immune checkpoint inhibitors (ICIs) have significantly altered the cancer treatment landscape in recent years, there is still room for improvement in the identification and management of patients that may benefit from ICIs. Identifying and applying biomarkers to predict disease response is crucial, and a recent review explored the currently available transcriptomic and clinical response data from ICI studies to provide insight on the current treatment landscape.
The review included clinical trial and study results in which ICIs were used, including transcriptomic data from whole blood samples, fresh-frozen tissue, and formalin-fixed paraffin-embedded tissue. The review involved 26 datasets, including 2386 samples from 1830 patients.
ICIs targeting several checkpoints are currently approved. Ipilimumab targets cytotoxic T lymphocyte-associated protein 4 (CTLA-4); nivolumab, pembrolizumab, and cemiplimab target programmed cell death 1 (PD-1); and avelumab, atezolizumab,and durvalumab target programmed cell death ligand 1 (PD-L1) signaling pathway. Combination ipilimumab and nivolumab is also approved in certain cancer types. Another anti–CTLA-4 agent, tremelimumab, is not yet approved but received FDA Orphan Drug Designation for malignant melanoma and was granted priority review by the FDA in combination with durvalumab.
While only a small number of patients benefit from ICIs, they have clinical indications in 19 different types of cancer and 2 tissue-agnostic indications. Identifying biomarkers is a key initiative to allow for more effective clinical trials and to identify patients in the clinical setting who may respond to ICIs. Pembrolizumab, nivolumab, and atezolizumab, for example, require PD-L1 expression ahead of treatment.
The question of whether adjuvant or neoadjuvant settings are ideal timing for ICI treatment is also being explored, as well as whether simultaneous chemotherapy and/or radiotherapy is more beneficial. These strategies vary based on tumor types, stages, and other factors, and there is no universal protocol for all patients.
In advanced esophageal squamous cell carcinoma, neoadjuvant chemoradiotherapy plus adjuvant nivolumab led to longer disease-free survival. In melanoma, however, some studies suggest neoadjuvant ICI treatment is the better strategy. There are still many ongoing trials addressing this aspect of treatment.
More than 10 studies covering anti–PD-1 monotherapy in solid tumors were included in the review, which produced more datasets than any other disease type. Pembrolizumab is applicable across many cancer types, although response rates can be low even when PD-L1 expression is measured as a predictive marker. Seven studies that covered anti–PD-1 monotherapy in melanoma specifically were included, highlighting several potential markers in this setting.
Five studies included data on anti–PD-L1 monotherapy, all in solid tumors. The largest dataset found that PD-L1 expression on immune cells but not in tumor cells was associated with improved atezolizumab response in metastatic urothelial cancer.
There were 3 studies involving anti–CTLA-4 monotherapy, with ipilimumab studies showing more favorable results than tremelimumab outcomes in patients with melanoma. Combination anti–PD-1 and anti–CTLA-4 therapy is rare, and only 3 published studies place a focus on it, the authors noted.
The review is limited by the fact that clinical trials of a new generation of ICIs are currently ongoing and therefore do not have available linked transcriptomic datasets. This includes agents targeting TIM-3, LAG-3, CD276, B7-H4, A2aR, CD73, CD94, and PVRIG/PVRL2. But overall, the need for more markers to predict ICI effectiveness still remains.
“The number of retrospective studies investigating predictive biomarkers useful for immune checkpoint inhibitors is still low,” the authors concluded.“Our review was set up to enable the reader to be acquainted with transcriptome-level datasets while maintaining a bird’s eye view of the entire field. Selection and combination of the most relevant datasets will enable rapid independent validation of future biomarker candidates correlated to ICI therapy response.”
Kovács SA, Győrffy B. Transcriptomic datasets of cancer patients treated with immune-checkpoint inhibitors: a systematic review. J Transl Med. Published online May 31, 2022. doi:10.1186/s12967-022-03409-4