The toxicity associated with combining immune check point inhibitors with tyrosine kinase inhibitors in patients with non-small cell lung cancer

New promises and challenges in the treatment of advanced non-small-cell lung cancer

Targeted therapies and immunotherapies have radically improved treatment for advanced non-small-cell lung cancer (NSCLC). Tyrosine kinase inhibitors targeting oncogenic driver mutations continue to evolve over multiple generations to enhance effectiveness and tackle drug resistance. Immune checkpoint inhibitors remain integral for the treatment of NSCLCs that do not have specific actionable genetic mutations. Antibody-drug conjugates and bispecific antibodies are being integrated into treatment guidelines, and emerging therapies include T-cell engagers, cellular therapies, cancer vaccines, and external devices. Despite these advances, challenges remain in identifying predictive biomarkers to individually tailor treatments, abrogate resistance, reduce costs, and ensure optimal cancer treatment accessibility.

The more the merrier? Evidence and efficacy of immune checkpoint- and tyrosine kinase inhibitor combinations in advanced solid cancers

Immune checkpoint inhibitors (ICI) and tyrosine kinase inhibitors (TKI) have gained therapeutical significance in cancer therapy over the last years. Due to the high efficacy of each substance group, additive or complementary effects are considered, and combinations are the subject of multiple prospective trials in different tumor entities. The majority of available data results from clinical phase I and II trials. Although regarded as well-tolerated therapies ICI-TKI combinations have higher toxicities compared to monotherapies of one of the substance classes and some combinations were shown to be excessively toxic leading to discontinuation of trials. So far, ICI-TKI combinations with nivolumab + cabozantinib, pembrolizumab + axitinib, avelumab + axitinib, pembrolizumab + lenvatinib have been approved in advanced renal cell (RCC), with pembrolizumab + lenvatinib in endometrial carcinoma and with camrelizumab + rivoceranib in hepatocellular carcinoma (HCC). Several ICI-TKI combinations are currently investigated in phase I to III trials in various other cancer entities. Further, the optimal sequence of ICI-TKI combinations is an important subject of investigation, as cross-resistances between the substance classes were observed. This review reports on clinical trials with ICI-TKI combinations in different cancer entities, their efficacy and toxicity.

AI/ML advances in non-small cell lung cancer biomarker discovery

Lung cancer is the leading cause of cancer deaths among both men and women, representing approximately 25% of cancer fatalities each year. The treatment landscape for non-small cell lung cancer (NSCLC) is rapidly evolving due to the progress made in biomarker-driven targeted therapies. While advancements in targeted treatments have improved survival rates for NSCLC patients with actionable biomarkers, long-term survival remains low, with an overall 5-year relative survival rate below 20%. Artificial intelligence/machine learning (AI/ML) algorithms have shown promise in biomarker discovery, yet NSCLC-specific studies capturing the clinical challenges targeted and emerging patterns identified using AI/ML approaches are lacking. Here, we employed a text-mining approach and identified 215 studies that reported potential biomarkers of NSCLC using AI/ML algorithms. We catalogued these studies with respect to BEST (Biomarkers, EndpointS, and other Tools) biomarker sub-types and summarized emerging patterns and trends in AI/ML-driven NSCLC biomarker discovery. We anticipate that our comprehensive review will contribute to the current understanding of AI/ML advances in NSCLC biomarker research and provide an important catalogue that may facilitate clinical adoption of AI/ML-derived biomarkers.