Quantification of biomarker functionality predicts patient outcomes

Programmed Death Ligand-1 and Tumor Mutation Burden Testing of Patients With Lung Cancer for Selection of Immune Checkpoint Inhibitor Therapies: Guideline From the College of American Pathologists, Association for Molecular Pathology, International Association for the Study of Lung Cancer, Pulmonary Pathology Society, and LUNGevity Foundation

CONTEXT.—

Rapid advancements in the understanding and manipulation of tumor-immune interactions have led to the approval of immune therapies for patients with non-small cell lung cancer. Certain immune checkpoint inhibitor therapies require the use of companion diagnostics, but methodologic variability has led to uncertainty around test selection and implementation in practice.

OBJECTIVE.—

To develop evidence-based guideline recommendations for the testing of immunotherapy/immunomodulatory biomarkers, including programmed death ligand-1 (PD-L1) and tumor mutation burden (TMB), in patients with lung cancer.

DESIGN.—

The College of American Pathologists convened a panel of experts in non-small cell lung cancer and biomarker testing to develop evidence-based recommendations in accordance with the standards for trustworthy clinical practice guidelines established by the National Academy of Medicine. A systematic literature review was conducted to address 8 key questions. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach, recommendations were created from the available evidence, certainty of that evidence, and key judgments as defined in the GRADE Evidence to Decision framework.

RESULTS.—

Six recommendation statements were developed.

CONCLUSIONS.—

This guideline summarizes the current understanding and hurdles associated with the use of PD-L1 expression and TMB testing for immune checkpoint inhibitor therapy selection in patients with advanced non-small cell lung cancer and presents evidence-based recommendations for PD-L1 and TMB testing in the clinical setting.

Determination of Interactive States of Immune Checkpoint Regulators in Lung Metastases after Radiofrequency Ablation

BACKGROUND

Cases of the spontaneous regression of multiple pulmonary metastases, after radiofrequency ablation (RFA), of a single lung metastasis, have been documented to be mediated by the immune system. The interaction of immune checkpoints, e.g., PD-1/PD-L1 and CTLA-4/CD80, may explain this phenomenon. The purpose of this study is to identify and quantify immune mechanisms triggered by RFA of pulmonary metastases originating from colorectal cancer.

METHODS

We used two-site time-resolved Förster resonance energy transfer as determined by frequency-domain FLIM (iFRET) for the quantification of receptor-ligand interactions. iFRET provides a method by which immune checkpoint interaction states can be quantified in a spatiotemporal manner. The same patient sections were used for assessment of ligand-receptor interaction and intratumoral T-cell labeling.

CONCLUSION

The checkpoint interaction states quantified by iFRET did not correlate with ligand expression. We show that immune checkpoint ligand expression as a predictive biomarker may be unsuitable as it does not confirm checkpoint interactions. In pre-RFA-treated metastases, there was a significant and negative correlation between PD-1/PD-L1 interaction state and intratumoral CD3+ and CD8+ density. The negative correlation of CD8+ and interactive states of PD-1/PD-L1 can be used to assess the state of immune suppression in RFA-treated patients.

From rough to precise: PD-L1 evaluation for predicting the efficacy of PD-1/PD-L1 blockades

Developing biomarkers for accurately predicting the efficacy of immune checkpoint inhibitor (ICI) therapies is conducive to avoiding unwanted side effects and economic burden. At the moment, the quantification of programmed cell death ligand 1 (PD-L1) in tumor tissues is clinically used as one of the combined diagnostic assays of response to anti-PD-1/PD-L1 therapy. However, the current assays for evaluating PD-L1 remain imperfect. Recent studies are promoting the methodologies of PD-L1 evaluation from rough to precise. Standardization of PD-L1 immunohistochemistry tests is being promoted by using optimized reagents, platforms, and cutoff values. Combining novel in vivo probes with PET or SPECT will probably be of benefit to map the spatio-temporal heterogeneity of PD-L1 expression. The dynamic change of PD-L1 in the circulatory system can also be realized by liquid biopsy. Consider PD-L1 expressed on non-tumor (immune and non-immune) cells, and optimized combination detection indexes are further improving the accuracy of PD-L1 in predicting the efficacy of ICIs. The combinations of artificial intelligence with novel technologies are conducive to the intelligence of PD-L1 as a predictive biomarker. In this review, we will provide an overview of the recent progress in this rapidly growing area and discuss the clinical and technical challenges.