EGFR Inhibition by Cetuximab Modulates Hypoxia and IFN Response Genes in Head and Neck Squamous Cell Carcinoma

Phase Ib trial of IRX-2 plus durvalumab in patients with recurrent and/or metastatic head and neck squamous cell carcinoma

OBJECTIVES

IRX-2 is a multi-cytokine immune-activating agent with anti-tumor activity in non-metastatic head and neck squamous cell carcinoma (HNSCC). Here, we evaluated combined IRX-2 and durvalumab in patients with recurrent and/or metastatic HNSCC.

MATERIALS AND METHODS

This was a phase Ib trial consisting of dose escalation and expansion. Primary endpoints were safety and biomarkers to assess the immune response in the tumor microenvironment including significant increases in PD-L1 expression and CD8 + tumor infiltrating lymphocytes (TIL) comparing pre- and on-treatment tumor biopsies. Secondary endpoints were objective response rates (ORR) and survival outcomes.

RESULTS

Sixteen patients were evaluable for response, and nine patients were evaluable for biomarkers. Thirteen patients (68 %) had exposure to prior anti-PD-1 therapy. No dose-limiting or grade ≥ 3 treatment-related adverse events were observed. On-treatment biopsies showed significantly increased PD-L1 (p = 0.005), CD3+ (p = 0.020), CD4+ (p = 0.022), and CD8 + T cells (p = 0.017) compared to pre-treatment. Median overall survival and progression-free survival (PFS) were 6.18 months (95 % CI, 2.66-8.61) and 2.53 months (95 % CI, 1.81-4.04), respectively. One patient had an objective response (ORR, 5.3 %) with an ongoing PFS of > 25 months. Disease control rate was 42 %. The responder harbored an ARID1A variant of unknown significance (VUS) that was predicted to bind her HLA-I alleles with a higher affinity than the reference peptide.

CONCLUSIONS

IRX-2 and durvalumab were safe and elicited the evidence of immune activation in the tumor microenvironment determined by increased PD-L1 expression and CD8+ TILs.

CLINICAL TRIAL REGISTRATION NUMBER

NCT03381183.

Cetuximab chemotherapy resistance: Insight into the homeostatic evolution of head and neck cancer (Review)

The complex evolution of genetic alterations in cancer that occurs in vivo is a selective process involving numerous factors and mechanisms. Chemotherapeutic agents that prevent the growth and spread of cancer cells induce selective pressure, leading to rapid artificial selection of resistant subclones. This rapid evolution is possible because antineoplastic drugs promote alterations in tumor‑cell metabolism, thus creating a bottleneck event. The few resistant cells that survive in this new environment obtain differential reproductive success that enables them to pass down the newly selected resistant gene pool. The present review aims to summarize key findings of tumor evolution, epithelial‑mesenchymal transition and resistance to cetuximab therapy in head and neck squamous cell carcinoma.

Spatial interactions modulate tumor growth and immune infiltration

Lenia, a cellular automata framework used in artificial life, provides a natural setting to implement mathematical models of cancer incorporating features such as morphogenesis, homeostasis, motility, reproduction, growth, stimuli response, evolvability, and adaptation. Historically, agent-based models of cancer progression have been constructed with rules that govern birth, death and migration, with attempts to map local rules to emergent global growth dynamics. In contrast, Lenia provides a flexible framework for considering a spectrum of local (cell-scale) to global (tumor-scale) dynamics by defining an interaction kernel governing density-dependent growth dynamics. Lenia can recapitulate a range of cancer model classifications including local or global, deterministic or stochastic, non-spatial or spatial, single or multi-population, and off or on-lattice. Lenia is subsequently used to develop data-informed models of 1) single-population growth dynamics, 2) multi-population cell-cell competition models, and 3) cell migration or chemotaxis. Mathematical modeling provides important mechanistic insights. First, short-range interaction kernels provide a mechanism for tumor cell survival under conditions with strong Allee effects. Next, we find that asymmetric interaction tumor-immune kernels lead to poor immune response. Finally, modeling recapitulates immune-ECM interactions where patterns of collagen formation provide immune protection, indicated by an emergent inverse relationship between disease stage and immune coverage.

Spatial interactions modulate tumor growth and immune infiltration

Direct observation of immune cell trafficking patterns and tumor-immune interactions is unlikely in human tumors with currently available technology, but computational simulations based on clinical data can provide insight to test hypotheses. It is hypothesized that patterns of collagen formation evolve as a mechanism of immune escape, but the exact nature of the interaction between immune cells and collagen is poorly understood. Spatial data quantifying the degree of collagen fiber alignment in squamous cell carcinomas indicates that late stage disease is associated with highly aligned fibers. Here, we introduce a computational modeling framework (called Lenia) to discriminate between two hypotheses: immune cell migration that moves 1) parallel or 2) perpendicular to collagen fiber orientation. The modeling recapitulates immune-ECM interactions where collagen patterns provide immune protection, leading to an emergent inverse relationship between disease stage and immune coverage. We also illustrate the capabilities of Lenia to model the evolution of tumor progression and immune predation. Lenia provides a flexible framework for considering a spectrum of local (cell-scale) to global (tumor-scale) dynamics by defining a kernel cell-cell interaction function that governs tumor growth dynamics under immune predation with immune cell migration. Mathematical modeling provides important mechanistic insights into cell interactions. Short-range interaction kernels provide a mechanism for tumor cell survival under conditions with strong Allee effects, while asymmetric tumor-immune interaction kernels lead to poor immune response. Thus, the length scale of tumor-immune interactions drives tumor growth and infiltration.

Immune Assessment Today: Optimizing and Standardizing Efforts to Monitor Immune Responses in Cancer and Beyond

As part of a symposium, current and former directors of Immune Monitoring cores and investigative oncologists presented insights into the past, present and future of immune assessment. Dr. Gnjatic presented a classification of immune monitoring technologies ranging from universally applicable to experimental protocols, while emphasizing the need for assay harmonization. Dr. Obeng discussed physiologic differences among CD8 T cells that align with anti-tumor responses. Dr. Lyerly presented the Soldano Ferrone lecture, commemorating the passionate tumor immunologist who inspired many, and covered a timeline of monitoring technology development and its importance to immuno-oncology. Dr. Sonabend presented recent achievements in glioblastoma treatment, accentuating the range of monitoring techniques that allowed him to refine patient selection for clinical trials. Dr. Guevara-Patiño focused on hypoxia within the tumor environment and stressed that T cell viability is not to be confused with functionality. Dr. Butterfield accentuated monitoring of dendritic cell metabolic (dys)function as a determinant for tumor vaccine success. Lectures were interspersed with select abstract presentations. To summarize the concepts, Dr. Maecker from Stanford led an informative forum discussion, pointing towards the future of immune monitoring. Immune monitoring continues to be a guiding light towards effective immunotherapeutic strategies.

Deciphering the Tumor-Immune-Microbe Interactions in HPV-Negative Head and Neck Cancer

Patients with human papillomavirus-negative head and neck squamous cell carcinoma (HPV-negative HNSCC) have worse outcomes than HPV-positive HNSCC. In our study, we used a published dataset and investigated the microbes enriched in molecularly classified tumor groups. We showed that microbial signatures could distinguish Hypoxia/Immune phenotypes similar to the gene expression signatures. Furthermore, we identified three highly-correlated microbes with immune processes that are crucial for immunotherapy response. The survival of patients in a molecularly heterogenous group shows significant differences based on the co-abundance of the three microbes. Overall, we present evidence that tumor-associated microbiota are critical components of the tumor ecosystem that may impact tumor microenvironment and immunotherapy response. The results of our study warrant future investigation to experimentally validate the conclusions, which have significant impacts on clinical decision-making, such as treatment selection.