In 2019, the FDA approved pembrolizumab, a monoclonal antibody targeting PD-1, for the first-line treatment of recurrent or metastatic head and neck cancers, despite only a limited number of patients benefiting from the treatment. Promising effects of therapeutic vaccination led the FDA to approve the use of the first therapeutic vaccine in prostate cancer in 2010. Research in the field of therapeutic vaccination, including possible synergistic effects with anti-PD(L)1 treatments, is evolving each year, and many vaccines are in pre-clinical and clinical studies. The aim of this review article is to discuss vaccines as a new therapeutic strategy, particularly in the field of head and neck cancers. Different vaccination technologies are discussed, as well as the results of the first clinical trials in HPV-positive, HPV-negative, and EBV-induced head and neck cancers.

Background The viral pandemic coronavirus disease 2019 (COVID-19) has disrupted cancer patient management around the world. Most reported data relate to incidence, risk factors, and outcome of severe COVID-19. The safety of systemic anti-cancer therapy in oncology patients with non-severe COVID-19 is an important matter in daily practice. Methods ONCOSARS-1 was a single-center, academic observational study. Adult patients with solid tumors treated in the oncology day unit with systemic anti-cancer therapy during the initial phase of the COVID-19 pandemic in Belgium were prospectively included. All patients (n = 363) underwent severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) serological testing after the first peak of the pandemic in Belgium. Additionally, 141 of these patients also had a SARS-CoV-2 RT-PCR test during the pandemic. The main objective was to retrospectively determine the safety of systemic cancer treatment, measured by the rate of adverse events according to the Common Terminology Criteria for Adverse Events, in SARS-CoV-2-positive patients compared with SARS-CoV-2-negative patients. Results Twenty-two (6%) of the 363 eligible patients were positive for SARS-CoV-2 by RT-PCR and/or serology. Of these, three required transient oxygen supplementation, but none required admission to the intensive care unit. Hematotoxicity was the only adverse event more frequently observed in SARS-CoV-2 -positive patients than in SARS-CoV-2-negative patients: 73% vs 35% (P < 0.001). This association remained significant (odds ratio (OR) 4.1, P = 0.009) even after adjusting for performance status and type of systemic treatment. Hematological adverse events led to more treatment delays for the SARS-CoV-2-positive group: 55% vs 20% (P < 0.001). Median duration of treatment interruption was similar between the two groups: 14 and 11 days, respectively. Febrile neutropenia, infections unrelated to COVID-19, and bleeding events occurred at a low rate in the SARS-CoV-2-positive patients. Conclusion Systemic anti-cancer therapy appeared safe in ambulatory oncology patients treated during the COVID-19 pandemic. There were, however, more treatment delays in the SARS-CoV-2-positive population, mainly due to a higher rate of hematological adverse events.

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The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending on its composition and the interactions between cancer cells and peri-tumoral cells, the TME may affect cancer progression. The characterization of tumors and their complex microenvironment could improve the understanding of cancer diseases and may help scientists and clinicians to discover new biomarkers.We recently developed several multiplex immunofluorescence (mIF) panels based on tyramide signal amplification (TSA) for the characterization of the TME in colorectal cancer, head and neck squamous cell carcinoma, melanoma, and lung cancer. Once the staining and scanning of the corresponding panels are completed, the samples are analyzed on an image analysis software. The spatial position and the staining of each cell are then exported from this quantification software into R. We developed R scripts that allow us not only to analyze the density of each cell type in several tumor compartments (e.g. the center of the tumor, the margin of the tumor, and the stroma) but also to perform distance-based analyses between different cell types.This particular workflow adds a spatial dimension to the classical density analysis already routinely performed for several markers. mIF analysis could allow scientists to have a better understanding of the complex interaction between cancer cells and the TME and to discover new predictive biomarkers of response to treatments, such as immune checkpoint inhibitors, and targeted therapies.