This Research Topic is the third volume of the “Community Series in the Role of Angiogenesis and Immune Response in Tumor Microenvironment of Solid Tumor" series. Please see Volume I <a href="https://www.frontiersin.org/research-topics/32467/the-role-of-angiogenesis-and-immune-response-in-tumor-microenvironment-of-solid-tumor#authors">here</a>, and Volume II <a href="https://www.frontiersin.org/research-topics/45499/community-series-in-the-role-of-angiogenesis-and-immune-response-in-tumor-microenvironment-of-solid-tumor-volume-ii>here</a>. The microenvironment of tumors is consisted of the tumor stroma, proliferating tumor cells, infiltrating inflammatory cells, blood vessels, and various associated tissue cells. The pre-metastatic niche (PRN) is described as supportive and receptive, which undergoes cellular and molecular changes to form the fertile “soil” or metastatic-designated sites for metastatic tumor cell “seed” colonization. Thus, the PRN supports promoting tumor metastasis and tumor settlement in distant organs. The infiltration of the immune cells and the formation of blood vessels from the pre-metastatic sites are critical for the tumor microenvironment. Typically, the angiogenic factor is strongly associated with the inflammatory response during the development of tumors. Additionally, the immunoediting processes are essentially devoted to promoting angiogenesis and modulating the innate and specific immune responses. In this research topic, we would like to share new findings and discussions on the role of angiogenesis and immune response in the tumor microenvironment of solid tumors. We welcome Review, Original Research, and Method articles in the following subtopics: 1) Novel mechanisms or targets connected with immune response and angiogenesis in solid tumors. 2) Tumor variation of angiogenesis and immune system. 3) Therapeutic advances impacting the immune system and angiogenesis in solid tumors. 4) Association of tumor-infiltrating immune cells on cancer. 5) Influence of anti-angiogenic normalization that advances the evolution of the immune system. Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation are considered out of scope of this section.

Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University

University of Notre Dame

First Affiliated Hospital of Anhui Medical University

Frontiers in Immunology

Cancer Immunity and Immunotherapy

Frontiers in Oncology

Community Series in the Role of Angiogenesis and Immune Response in Tumor Microenvironment of Solid Tumor: Volume III

Tumorogenesis is characterized by the unregulated proliferation of cells, which is the consequence of dysregulated cell division mechanisms. To ensure rapid multiplication and invasion, a tumor tends to create a unique tumor microenvironment (TME) benefiting its own progression. As an abnormal component in the body, figuring out how to escape from the supervision and attack of the immune system is key to tumor survival. Angiogenesis, which is mainly triggered by the stimulation of vascular endothelial growth factor (VEGF), is one of its solutions. Characterized by hypoxia, most types of tumor cells significantly upregulate VEGF, which stimulates the active construction of tumor neovascularization (<a href="#B1">1</a>–<a href="#B3">3</a>). However, the newly formed tumor blood vessels show a series of abnormalities, including increased luminal resistance, increased endothelial permeability, and limited blood flow caused by defects in structure (<a href="#B4">4</a>). The features above are beneficial to tumor growth and metastasis as well as immune evasion, inducing resistance to immunotherapy. It was reported that anti-angiogenesis therapy has been seen as a promising strategy to enhance tumor immune response, which contributes to improving immunosuppressive TME and aids the immune system’s anti-tumor effects (<a href="#B5">5</a>–<a href="#B7">7</a>).The relation between angiogenesis and immune response was revealed at the gene and transcriptomic level. <a href="https://doi.org/10.3389/fimmu.2023.1215607">Kurmyshkina et&nbsp;al.</a> have focused on the difference in transcriptomic landscapes between early-stage invasive cervical carcinoma (CeCa) and cervical intraepithelial neoplastic lesions (CIN). The authors found that innate immune pathways in early-stage CeCa were significantly upregulated in response to the infection of human papillomavirus compared with CIN as precursor lesions. The tumors with active immune infiltration showed a more differentiated phenotype, while the ones with increased expression of genes associated with angiogenesis were related to exacerbation of de-differentiation and epithelial-to-mesenchymal transition. As reported, anti-angiogenesis therapy was expected to improve immune evasion and enhance immune infiltration. <a href="https://doi.org/10.3389/fimmu.2023.1200941">Shafqat et&nbsp;al.</a> have summarized previous studies that focused on tumor angiogenesis and coagulation exhibiting suppressive effects on the anti-tumor immune response. Both mediate the impacts above through specific mechanisms ultimately leading to the reprogramming of TME. The usage of anti-angiogenic therapies to achieve vascular normalization and ACEi/ARBs to achieve stromal normalization targeting angiogenesis, or anticoagulants targeting coagulation, showed similar results of limiting tumor progression and transforming TME to favor an immune response against tumors. Also, they both demonstrated the efficacy of enhancing immunotherapy while combining with ICIs even though the heterogeneity of tumor types still needs to be considered in conjunction. It is natural to associate angiogenesis with prognosis because of its influence on tumor invasion and progression. <a href="https://doi.org/10.3389/fimmu.2024.1414450">Li et&nbsp;al.</a> have developed an advanced machine learning model to evaluate the prognosis and therapy response of breast cancer based on several genes related to vascular mimicry (VM), the performance of which continuously exceeds that of traditional ones. The tumor group received higher VM scores than the normal group. The high-risk group showed a higher level of tumor mutation burden (TMB), higher mutation rate of tumor suppressor genes, and higher level of immune escape, suggesting a poor response to immunotherapy at the same time. Meanwhile, the low-risk group appeared more favorable response to immune checkpoint blockage. Eventually, the authors identified several promising chemotherapy drugs to which VM-related genes were sensitive.To summarize, the studies above introduce some latest advances in the roles of angiogenesis and immune response in TME of solid tumors and hopefully contribute to the further exploration of immunotherapy enhancers. We would like to acknowledge the invaluable support of all authors, reviewers, and the editorial team during the topic preparation process. We are looking forward to the rapid emergence of significant breakthroughs in the approach of sensitizing immunotherapy through anti-angiogenesis agents.FZ: Writing &#x2013; original draft. ZC: Writing &#x2013; original draft. WJ: Writing &#x2013; review &amp; editing, Conceptualization. RZ: Writing &#x2013; review &amp; editing, Supervision, Funding acquisition.The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by National Natural Science Foundation of China, 82271766 (RZ).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Editorial: Community series in the role of angiogenesis and immune response in tumor microenvironment of solid tumor, volume III

BackgroundIn the ongoing battle against breast cancer, a leading cause of cancer-related mortality among women globally, the urgent need for innovative prognostic markers and therapeutic targets is undeniable. This study pioneers an advanced methodology by integrating machine learning techniques to unveil a vascular mimicry signature, offering predictive insights into breast cancer outcomes. Vascular mimicry refers to the phenomenon where cancer cells mimic blood vessel formation absent of endothelial cells, a trait associated with heightened tumor aggression and diminished response to conventional treatments.</sec>MethodsThe study’s comprehensive analysis spanned data from over 6,000 breast cancer patients across 12 distinct datasets, incorporating both proprietary clinical data and single-cell data from 7 patients, accounting for a total of 43,095 cells. By employing an integrative strategy that utilized 10 machine learning algorithms across 108 unique combinations, the research scrutinized 100 existing breast cancer signatures. Empirical validation was sought through immunohistochemistry assays, alongside explorations into potential immunotherapeutic and chemotherapeutic avenues.</sec>ResultsThe investigation successfully identified six genes related to vascular mimicry from multi-center cohorts, laying the groundwork for a novel predictive model. This model outstripped the prognostic accuracy of traditional clinical and molecular indicators in forecasting recurrence and mortality risks. High-risk individuals identified by our model faced worse outcomes. Further validation through IHC assays in 30 patients underscored the model’s extensive applicability. Notably, the model unveiled varying therapeutic responses; low-risk patients might achieve greater benefits from immunotherapy, whereas high-risk patients demonstrated a particular sensitivity to certain chemotherapies, such as ispinesib.</sec>ConclusionsThis model marks a significant step forward in the precise evaluation of breast cancer prognosis and therapeutic responses across different patient groups. It heralds the possibility of refining patient outcomes through tailored treatment strategies, accentuating the potential of machine learning in revolutionizing cancer prognosis and management.</sec>

Background: In the ongoing battle against breast cancer, a leading cause of cancer-related mortality among women globally, the urgent need for innovative prognostic markers and therapeutic targets is undeniable. This study pioneers an advanced methodology by integrating machine learning techniques to unveil a vascular mimicry signature, offering predictive insights into breast cancer outcomes. Vascular mimicry refers to the phenomenon where cancer cells mimic blood vessel formation absent of endothelial cells, a trait associated with heightened tumor aggression and diminished response to conventional treatments.Methods: The study’s comprehensive analysis spanned data from over 6,000 breast cancer patients across 12 distinct datasets, incorporating both proprietary clinical data and single-cell data from 7 patients, accounting for a total of 43,095 cells. By employing an integrative strategy that utilized 10 machine learning algorithms across 108 unique combinations, the research scrutinized 100 existing breast cancer signatures. Empirical validation was sought through immunohistochemistry assays, alongside explorations into potential immunotherapeutic and chemotherapeutic avenues.Results: The investigation successfully identified six genes related to vascular mimicry from multi-center cohorts, laying the groundwork for a novel predictive model. This model outstripped the prognostic accuracy of traditional clinical and molecular indicators in forecasting recurrence and mortality risks. High-risk individuals identified by our model faced worse outcomes. Further validation through IHC assays in 30 patients underscored the model’s extensive applicability. Notably, the model unveiled varying therapeutic responses; low-risk patients might achieve greater benefits from immunotherapy, whereas high-risk patients demonstrated a particular sensitivity to certain chemotherapies, such as ispinesib.Conclusions: This model marks a significant step forward in the precise evaluation of breast cancer prognosis and therapeutic responses across different patient groups. It heralds the possibility of refining patient outcomes through tailored treatment strategies, accentuating the potential of machine learning in revolutionizing cancer prognosis and management.

Deciphering breast cancer prognosis: a novel machine learning-driven model for vascular mimicry signature prediction

BackgroundMolecular diversity of virus-associated cervical cancer remains a relatively underexplored issue, and interrelations of immunologic and angiogenic features during the establishment of a particular landscape of the cervical cancer microenvironment are not well-characterized, especially for its earliest clinical stages, although this may provide insight into the mechanisms behind the differences in tumor aggressiveness, treatment responsiveness and prognosis. In this research, we were aimed at identifying transcriptomic landscapes of early-stage cervical carcinoma that differ substantially in their immune-related characteristics, patterns of signaling pathways and composition of the microenvironment in comparison with immediate precursor (intraepithelial) lesions.</sec>MethodsWe performed the Illumina platform-based RNA sequencing using a panel of fresh tissue samples that included human papillomavirus-positive cervical intraepithelial neoplastic lesions (CIN), invasive squamous carcinoma of the cervix of FIGO IA1-IIB stages, and morphologically normal epithelium. The derived transcriptomic profiles were bioinformatically analyzed and compared by patterns of signaling pathway activation, distribution of tumor-infiltrating cell populations, and genomic regions involved.</sec>ResultAccording to hierarchical cluster analysis of the whole-transcriptome profiles, tissue samples were distributed between three groups, or gene expression patterns (the one comprising most pre-cancer cases and the other two encompassing mostly early-stage invasive cancer cases). Differentially expressed genes were retrieved in each intergroup pairwise comparison followed by Gene Ontology analysis. Gene set enrichment analysis of the two groups of tumor samples in comparison with the CIN group identified substantial differences in immunological and angiogenic properties between tumorous groups suggesting the development of different molecular phenotypes. Cell composition analysis confirmed the diverse changes in the abundancies of immune and non-immune populations and, accordingly, different impacts of the immune and stromal compartments on the tumor microenvironment in these two groups of tumors compared to CIN. Positional gene expression analysis demonstrated that the identified transcriptomic differences were linked to different chromosomal regions and co-localized with particular gene families implicated in immune regulation, inflammation, cell differentiation, and tumor invasion.</sec>ConclusionsOverall, detection of different transcriptomic patterns of invasive cervical carcinoma at its earliest stages supports the diverse impacts of immune response- and angiogenesis-related mechanisms on the onset of tumor invasion and progression. This may provide new options for broadening the applicability and increasing the efficiency of target anti-angiogenic and immune-based therapy of virus-associated cervical carcinoma.</sec>

Background: Molecular diversity of virus-associated cervical cancer remains a relatively underexplored issue, and interrelations of immunologic and angiogenic features during the establishment of a particular landscape of the cervical cancer microenvironment are not well-characterized, especially for its earliest clinical stages, although this may provide insight into the mechanisms behind the differences in tumor aggressiveness, treatment responsiveness and prognosis. In this research, we were aimed at identifying transcriptomic landscapes of early-stage cervical carcinoma that differ substantially in their immune-related characteristics, patterns of signaling pathways and composition of the microenvironment in comparison with immediate precursor (intraepithelial) lesions.Methods: We performed the Illumina platform-based RNA sequencing using a panel of fresh tissue samples that included human papillomavirus-positive cervical intraepithelial neoplastic lesions (CIN), invasive squamous carcinoma of the cervix of FIGO IA1-IIB stages, and morphologically normal epithelium. The derived transcriptomic profiles were bioinformatically analyzed and compared by patterns of signaling pathway activation, distribution of tumor-infiltrating cell populations, and genomic regions involved.Result: According to hierarchical cluster analysis of the whole-transcriptome profiles, tissue samples were distributed between three groups, or gene expression patterns (the one comprising most pre-cancer cases and the other two encompassing mostly early-stage invasive cancer cases). Differentially expressed genes were retrieved in each intergroup pairwise comparison followed by Gene Ontology analysis. Gene set enrichment analysis of the two groups of tumor samples in comparison with the CIN group identified substantial differences in immunological and angiogenic properties between tumorous groups suggesting the development of different molecular phenotypes. Cell composition analysis confirmed the diverse changes in the abundancies of immune and non-immune populations and, accordingly, different impacts of the immune and stromal compartments on the tumor microenvironment in these two groups of tumors compared to CIN. Positional gene expression analysis demonstrated that the identified transcriptomic differences were linked to different chromosomal regions and co-localized with particular gene families implicated in immune regulation, inflammation, cell differentiation, and tumor invasion.Conclusions: Overall, detection of different transcriptomic patterns of invasive cervical carcinoma at its earliest stages supports the diverse impacts of immune response- and angiogenesis-related mechanisms on the onset of tumor invasion and progression. This may provide new options for broadening the applicability and increasing the efficiency of target anti-angiogenic and immune-based therapy of virus-associated cervical carcinoma.

Sequencing-based transcriptome analysis reveals diversification of immune response- and angiogenesis-related expression patterns of early-stage cervical carcinoma as compared with high-grade CIN

Corrigendum: Reprogramming the immunosuppressive tumor microenvironment: exploiting angiogenesis and thrombosis to enhance immunotherapy

This review focuses on the immunosuppressive effects of tumor angiogenesis and coagulation on the tumor microenvironment (TME). We summarize previous research efforts leveraging these observations and targeting these processes to enhance immunotherapy outcomes. Clinical trials have documented improved outcomes when combining anti-angiogenic agents and immunotherapy. However, their overall survival benefit over conventional therapy remains limited and certain tumors exhibit poor response to anti-angiogenic therapy. Additionally, whilst preclinical studies have shown several components of the tumor coagulome to curb effective anti-tumor immune responses, the clinical studies reporting combinations of anticoagulants with immunotherapies have demonstrated variable treatment outcomes. By reviewing the current state of the literature on this topic, we address the key questions and future directions in the field, the answers of which are crucial for developing effective strategies to reprogram the TME in order to further the field of cancer immunotherapy.

This review focuses on the immunosuppressive effects of tumor angiogenesis and coagulation on the tumor microenvironment (TME). We summarize previous research efforts leveraging these observations and targeting these processes to enhance immunotherapy outcomes. Clinical trials have documented improved outcomes when combining anti-angiogenic agents and immunotherapy. However, their overall survival benefit over conventional therapy remains limited and certain tumors exhibit poor response to anti-angiogenic therapy. Additionally, whilst preclinical studies have shown several components of the tumor coagulome to curb effective anti-tumor immune responses, the clinical studies reporting combinations of anticoagulants with immunotherapies have demonstrated variable treatment outcomes. By reviewing the current state of the literature on this topic, we address the key questions and future directions in the field, the answers of which are crucial for developing effective strategies to reprogram the TME in order to further the field of cancer immunotherapy.