Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine

Prostate adenocarcinoma (PRAD) is a leading cause of death among men. Messenger ribonucleic acid (mRNA) vaccine presents an attractive approach to achieve satisfactory outcomes; however, tumor antigen screening and vaccination candidates show a bottleneck in this field. We aimed to investigate the tumor antigens for mRNA vaccine development and immune subtypes for choosing appropriate patients for vaccination. We identified eight overexpressed and mutated tumor antigens with poor prognostic value of PRAD, including KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3. The correlation of those genes with antigen-presenting immune cells were assessed. We further identified three immune subtypes of PRAD (PRAD immune subtype [PIS] 1–3) with distinct clinical, molecular, and cellular characteristics. PIS1 showed better survival and immune cell infiltration, nevertheless, PIS2 and PIS3 showed cold tumor features with poorer prognosis and higher tumor genomic instability. Moreover, these immune subtypes presented distinguished association with immune checkpoints, immunogenic cell death modulators, and prognostic factors of PRAD. Furthermore, immune landscape characterization unraveled the immune heterogeneity among patients with PRAD. To summarize, our study suggests KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3 are potential antigens for PRAD mRNA vaccine development, and patients in the PIS2 and PIS3 groups are more suitable for vaccination.

TAMI-31. GLIOBLASTOMA GENETIC DRIVERS DICTATE THE FUNCTION OF TUMOR-ASSOCIATED MACROPHAGES/MICROGLIA AND RESPONSES TO CSF1R INHIBITION

Tumor-associated macrophages/microglia (TAMs) are prominent microenvironment components in human glioblastoma (GBM) that are potential targets for anti-tumor therapy. However, TAM depletion by CSF1R inhibition showed mixed results in clinical trials. We hypothesized that GBM subtype-specific tumor microenvironment convey distinct sensitivities to TAM targeting. We generated syngeneic PDGFB-driven and RAS-driven GBM models that resemble proneural-like and mesenchymal-like gliomas, and determined the effect of TAM targeting by CSF1R inhibitor PLX3397 on glioma growth and progression. We also investigated the co-targeting of TAMs and angiogenesis on PLX3397-resistant RAS-driven GBM. Using single-cell transcriptomic profiling, we further explored differences in tumor microenvironment compositions and functions between the proneural-like and mesenchymal-like glioma models. We found that the growth of PDGFB-driven tumors was markedly inhibited by PLX3397. In contrast, depletion of TAMs at the early phase accelerated RAS-driven tumor growth and had no effects on other proneural and mesenchymal human GBM models. In addition, PLX3397-resistant RAS-driven tumors did not respond to PI3K signaling inhibition. Single-cell transcriptomic profiling revealed that PDGFB-driven gliomas induced expansion and activation of pro-tumor microglia, whereas mesenchymal RAS-driven gliomas elicited TAMs enriched in pro-inflammatory and angiogenic signaling. Co-targeting of TAMs and angiogenesis decreased cell proliferation and tumor mass in RAS-driven gliomas. Our work identifies functionally distinct TAM subpopulations in the growth of different glioma subtypes. Notably, we uncover a potential responsiveness of resistant mesenchymal-like gliomas to combined anti-angiogenic therapy and CSF1R inhibition. These data highlight the importance of microenvironment landscape characterization to optimally stratify glioma patients for TAM-targeted therapy.

GIS tools for landscape character assessment: case of Ziban region in Algeria

Landscape is an area formed by the interactions between humans and nature, which bring various characteristics to the area. Landscape Character Assessment (LCA) methods enable more accurate description, mapping, and evaluation of features within the landscape. Also, landscape characterization and classification is facilitated by the advances of Geographic Information Systems (GIS), which constitute a very efficient tool for analysis and overlay mapping. This paper explores and tests an application of Landscape Character Assessment (LCA) methodology at a regional scale in Ziban region, Algeria, combining natural and cultural attributes using GIS. The first stage of overlay of attributes is followed by the verification of draft map involving a visual assessment on-site in order to develop the final classification and assessment describing each landscape character area and type. The study results show that Ziban region has a rich structure with diversified landscapes created by unique natural and cultural landscape values composed of 36 different character areas and 19-character types. The main contribution of this research consists in developing a typology for Ziban landscape and providing useful results for decision-making related to the future management of landscape character in the Algerian context, which has undergone strong pressure related to urbanization, industry, transport, desertification, and tourism.