Immune Response to Locoregional Therapy

The immune response to cancer is an ongoing area of interest and is the focus of newer systemic agents. Liver-directed therapy has been the standard treatment for primary and metastatic disease limited to the liver. It is increasingly being recognized that these therapies may influence a broader systemic response and immune activation. The clinical and translational data supporting this phenomenon are reviewed herein. The findings and potential impact of the immune response to liver-directed therapies are summarized in this article.

Macroscopic limit of a kinetic model describing the switch in T cell migration modes via binary interactions

Experimental results on the immune response to cancer indicate that activation of cytotoxic T lymphocytes (CTLs) through interactions with dendritic cells (DCs) can trigger a change in CTL migration patterns. In particular, while CTLs in the pre-activation state move in a non-local search pattern, the search pattern of activated CTLs is more localised. In this paper, we develop a kinetic model for such a switch in CTL migration modes. The model is formulated as a coupled system of balance equations for the one-particle distribution functions of CTLs in the pre-activation state, activated CTLs and DCs. CTL activation is modelled via binary interactions between CTLs in the pre-activation state and DCs. Moreover, cell motion is represented as a velocity-jump process, with the running time of CTLs in the pre-activation state following a long-tailed distribution, which is consistent with a Lévy walk, and the running time of activated CTLs following a Poisson distribution, which corresponds to Brownian motion. We formally show that the macroscopic limit of the model comprises a coupled system of balance equations for the cell densities, whereby activated CTL movement is described via a classical diffusion term, whilst a fractional diffusion term describes the movement of CTLs in the pre-activation state. The modelling approach presented here and its possible generalisations are expected to find applications in the study of the immune response to cancer and in other biological contexts in which switch from non-local to localised migration patterns occurs.

From Anti-Severe Acute Respiratory Syndrome Coronavirus 2 Immune Response to Cancer Onset via Molecular Mimicry and Cross-Reactivity

Background and Objectives Whether exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may predispose to the risk of cancer in individuals with no prior cancers is a crucial question that remains unclear. To confirm/refute possible relationships between exposure to the virus and ex novo insurgence of tumors, this study analyzed molecular mimicry and the related cross-reactive potential between SARS-CoV-2 spike glycoprotein (gp) antigen and human tumor-suppressor proteins. Materials and Methods Tumor-associated proteins were retrieved from UniProt database and analyzed for pentapeptide sharing with SARS-CoV-2 spike gp by using publicly available databases. Results An impressively high level of molecular mimicry exists between SARS-CoV-2 spike gp and tumor-associated proteins. Numerically, 294 tumor-suppressor proteins share 308 pentapeptides with the viral antigen. Crucially, the shared peptides have a relevant immunologic potential by repeatedly occurring in experimentally validated epitopes. Such immunologic potential is of further relevancy in that most of the shared peptides are also present in infectious pathogens to which, in general, human population has already been exposed, thus indicating the possibility of immunologic imprint phenomena. Conclusion This article described a vast peptide overlap between SARS-CoV-2 spike gp and tumor-suppressor proteins, and supports autoimmune cross-reactivity as a potential mechanism underlying prospective cancer insurgence following exposure to SARS-CoV-2. Clinically, the findings call for close surveillance of tumor sequelae that possibly could result from the current coronavirus pandemic.

Clinical Significance of Expression of Immunoadjuvant Molecules (LAG-3, TIM-3, OX-40) in Neoadjuvant Chemotherapy for Breast Cancer

Purpose Various immunosuppressive factors that inhibit the immune response to cancer are present in cancer cells and the cancer microenvironment. Co-inhibitory and co-stimulatory receptors are dynamically expressed on T-cells as immunoadjuvant molecules that regulate the state of T-cell activity. In this report we focus on immunoadjuvant molecules such as LAG-3, TIM-3, and OX-40, for which there have been few published reports. We investigated the expression of LAG-3, TIM-3, and OX-40 in tumor-infiltrating lymphocytes (TILs), and clinically verified the significance of that expression in relation to neoadjuvant thermotherapy (NAC). Methods A total of 177 patients with resectable early-stage breast cancer were treated with NAC. Estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), Ki67, LAG-3, TIM-3 and OX-40 status were assessed by immunohistochemistry. Results There were 47 (26.6%) patients with high LAG-3 expression, 31 (17.5%) patients had high TIM-3 expression, and 32 (18.1%) patients had high OX-40 expression. The group with low-LAG-3 expression was significantly smaller than the group with high expression in triple-negative breast cancer (TNBC) (p = 0.038) and HER2-enriched breast cancer (HER2BC) (p = 0.021), and the total number of pathological complete response (pCR) patients was greater (p < 0.001). In TNBC and HER2BC, the pCR rate was significantly higher in the low-LAG-3 expression group than in the high-LAG-3 expression group (p < 0.001) (p = 0.020). Moreover, on multivariate analysis also showed that low-LAG-3 expression status was an independent factor to predict the favorable prognosis (p = 0.014, HR = 8.124) (p = 0.048, HR = 10.400). Conclusions Our findings suggest that LAG-3 may become a biomarker in highly malignant breast cancers such as TNBC and HER2BC that can predict the therapeutic efficacy of NAC.

Dendritic cells maintain anti-tumor immunity by positioning CD8 skin-resident memory T cells

Tissue-resident memory (TRM) T cells are emerging as critical components of the immune response to cancer; yet, requirements for their ongoing function and maintenance remain unclear. APCs promote TRM cell differentiation and re-activation but have not been implicated in sustaining TRM cell responses. Here, we identified a novel role for dendritic cells in supporting TRM to melanoma. We showed that CD8 TRM cells remain in close proximity to dendritic cells in the skin. Depletion of CD11c+ cells results in rapid disaggregation and eventual loss of melanoma-specific TRM cells. In addition, we determined that TRM migration and/or persistence requires chemotaxis and adhesion mediated by the CXCR6/CXCL16 axis. The interaction between CXCR6-expressing TRM cells and CXCL16-expressing APCs was found to be critical for sustaining TRM cell–mediated tumor protection. These findings substantially expand our knowledge of APC functions in TRM T-cell homeostasis and longevity.

The Role of Soluble LAG3 and Soluble Immune Checkpoints Profile in Advanced Head and Neck Cancer: A Pilot Study

Unresectable recurrent and/or metastatic head and neck squamous cell carcinoma (R/M HNSCC) has a very poor prognosis. Soluble immune checkpoints (sICs) are circulating proteins that result from the alternative splicing of membrane proteins and can modulate the immune response to cancer cells. The aim of our pilot study was to determine the possible role of a comprehensive evaluation of sICs in the classification of prognosis and response to treatment in patients with advanced disease. We evaluated several sICs (CD137, CTLA-4, PD-1, PD-L1, PD-L2, TIM3, LAG3, GITR, HVEM, BTLA, IDO, CD80, CD27, and CD28) from peripheral blood at baseline and investigated the association with clinical characteristics and outcomes. A high baseline soluble LAG3 (sLAG3 > 377 pg/mL) resulted in an association with poor PFS and OS (p = 0.047 and p = 0.003, respectively). Moreover, sLAG3 emerged as an independent prognostic factor using an MVA (p = 0.005). The evaluation of sICs, in particular sLAG3, may be relevant for identifying patients with worse prognoses, or resistance to treatments, and may lead to the development of novel targeted strategies.