Pretreatment neutrophil-to-lymphocyte ratio as a marker of outcomes in nivolumab-treated patients with advanced non-small-cell lung cancer

Predicting response and toxicity to immune checkpoint inhibitors using routinely available blood and clinical markers

Immune checkpoint inhibitors (ICI) are an important development in the treatment of advanced cancer. A substantial proportion of patients treated with ICI do not respond, and additionally patients discontinue treatment due to adverse effects. While many novel biological markers related to the specific mechanisms of ICI actions have been investigated, there has also been considerable research to identify routinely available blood and clinical markers that may predict response to ICI therapy. If validated, these markers have the advantage of being easily integrated into clinical use for nominal expense. Several markers have shown promise, including baseline and post-treatment changes in leucocyte counts, lactate dehydrogenase and C-reactive protein. While promising, the results between studies have been inconsistent due to small sample sizes, follow-up time and variability in the assessed markers. To date, research on routinely available blood and clinical markers has focussed primarily on ICI use in melanoma, the use of ipilimumab and on univariate associations, but preliminary evidence is emerging for other cancer types, other ICIs and for combining markers in multivariable clinical prediction models.

Cancer-Related Systemic Inflammation: The Challenges and Therapeutic Opportunities for Personalized Medicine

Over the last decade there has been significant progress towards the development of personalized or "precision" medicine for many patients with cancer. However, there still remain subpopulations of cancer patients that do not possess a tumor mutation profile that is successfully targeted by the newer molecular anticancer drugs and further personalized approaches are needed. The presence of cancer-related systemic inflammation represents an underappreciated subpopulation of cancer patients needing personalized therapy. For ∼25% of all advanced cancer patients, regardless of histological subtype, the patients with systemic inflammation have significantly poorer response to chemotherapy and also shorter overall survival compared to those cancer patients without inflammation. The development of cancer-related systemic inflammation involves interactions between host and tumor cells that are potential new drug targets in cancer chemotherapy. In this review we discuss the challenges and clinical opportunities to develop new therapeutic strategies for this underappreciated drug target.

Clinical characteristics of patient selection and imaging predictors of outcome in solid tumors treated with checkpoint-inhibitors

The rapidly evolving knowledge on tumor immunology and the continuous implementation of immunotherapy in cancer have recently led to the FDA and EMA approval of several checkpoint inhibitors as immunotherapic agents in clinical practice. Anti-CTLA-4, anti-PD-1, and anti-PDL-1 antibodies are becoming standard of care in advanced melanoma, as well as in relapsed or metastatic lung and kidney cancer, demonstrating higher and longer response compared to standard chemotherapy. These encouraging results have fostered the evaluation of these antibodies either alone or in combination with other therapies in several dozen clinical trials for the treatment of multiple tumor types. However, not all patients respond to immune checkpoint inhibitors, hence, specific biomarkers are necessary to guide and monitor therapy. The utility of PD-L1 expression as a biomarker has varied in different clinical trials, but, to date, no consensus has been reached on whether PD-L1 expression is an ideal marker for response and patient selection; approximately 20-25% of patients will respond to immunotherapy with checkpoint inhibitors despite a negative PD-L1 staining. On the other hand, major issues concern the evaluation of objective response in patients treated with immunotherapy. Pure morphological criteria as commonly used in solid tumors (i.e. RECIST) are not sufficient because change in size is not an early and reliable marker of tumor response to biological therapies. Thus, the scientific community has required a continuous adaptation of immune-related response criteria (irRC) to overcome the problem. In this context, metabolic information and antibody-based imaging with positron emission tomography (PET) have been investigated, providing a powerful approach for an optimal stratification of patients at staging and during the evaluation of the response to therapy. In the present review we provide an overview on the clinical characteristics of patient selection when using imaging predictors of outcome in solid tumors treated with checkpoint-inhibitors.