Clinical-genomic determinants of immune checkpoint blockade response in head and neck squamous cell carcinoma

A joint physics and radiobiology DREAM team vision - Towards better response prediction models to advance radiotherapy

Radiotherapy developed empirically through experience balancing tumour control and normal tissue toxicities. Early simple mathematical models formalized this practical knowledge and enabled effective cancer treatment to date. Remarkable advances in technology, computing, and experimental biology now create opportunities to incorporate this knowledge into enhanced computational models. The ESTRO DREAM (Dose Response, Experiment, Analysis, Modelling) workshop brought together experts across disciplines to pursue the vision of personalized radiotherapy for optimal outcomes through advanced modelling. The ultimate vision is leveraging quantitative models dynamically during therapy to ultimately achieve truly adaptive and biologically guided radiotherapy at the population as well as individual patient-based levels. This requires the generation of models that inform response-based adaptations, individually optimized delivery and enable biological monitoring to provide decision support to clinicians. The goal is expanding to models that can drive the realization of personalized therapy for optimal outcomes. This position paper provides their propositions that describe how innovations in biology, physics, mathematics, and data science including AI could inform models and improve predictions. It consolidates the DREAM team's consensus on scientific priorities and organizational requirements. Scientifically, it stresses the need for rigorous, multifaceted model development, comprehensive validation and clinical applicability and significance. Organizationally, it reinforces the prerequisites of interdisciplinary research and collaboration between physicians, medical physicists, radiobiologists, and computational scientists throughout model development. Solely by a shared understanding of clinical needs, biological mechanisms, and computational methods, more informed models can be created. Future research environment and support must facilitate this integrative method of operation across multiple disciplines.

Host-related indexes in head and neck cancer

PURPOSE OF REVIEW

Peripheral blood host-related indexes have been widely studied in cancer patients. Several authors have shown the prognostic capacity of these indexes in head and neck cancer. Therefore, there has been an increasing interest in this topic recently.

RECENT FINDINGS

The main variables analyzed and used to create these host-related indexes are peripheral blood leukocytes - including neutrophils, monocytes and lymphocytes - albumin and hemoglobin levels. Other factors with proven prognostic capacity in some studies are: platelets, C-reactive protein, and BMI. Among all the combined indexes, the neutrophil-to-lymphocyte ratio has been the most accepted and used worldwide. Nonetheless, there are other indexes which group multiple of these factors that have shown better prognostic capacity, and are promising in the near future.

SUMMARY

Host-related indexes are ideal biomarkers to be used on our daily-basis. There is enough evidence to start considering them when assessing patients with head and neck cancer.

Tumor mutational burden predictability in head and neck squamous cell carcinoma patients treated with immunotherapy: systematic review and meta-analysis

BACKGROUND

Tumor mutational burden (TMB) has been demonstrated to predict the response to immune checkpoint inhibitors (ICIs) in various cancers. However, the role of TMB in head and neck squamous cell carcinoma (HNSCC) has not yet been specifically addressed. Since HNSCC patients exhibit a rather limited response to ICIs, there is an unmet need to develop predictive biomarkers to improve patient selection criteria and the clinical benefit of ICI treatment.

METHODS

We conducted a systematic review and meta-analysis according to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. HNSCC cohort studies were selected when TMB prior to ICI treatment was evaluated, TMB cutoff value was available, and the prognostic value of TMB was evaluated by time-to-event survival analysis. A total of 11 out of 1960 articles were analyzed, including 1200 HNSCC patients.

RESULTS

The results showed that those patients harboring high TMB exhibited a significantly superior overall response rate (OR = 2.62; 95% CI 1.74-3.94; p < 0.0001) and a survival advantage (HR = 0.53; 95% CI 0.39-0.71; p < 0.0001) after ICI treatment.

CONCLUSION

This is the first meta-analysis to demonstrate a higher response and clinical benefit from ICI therapy in HNSCC patients with high TMB.