Heterogeneous Tumor-Immune Microenvironments among Differentially Growing Metastases in an Ovarian Cancer Patient

Computational studies reveal co-occurrence of two mutations in IL7R gene of high-grade serous carcinoma patients

Major cause of mortality in ovarian cancer can be attributed to a lack of specific and sensitive biomarkers for diagnosis and prognosis of the disease. Uncovering the mutations in genes involved in crucial oncogenic pathways is a key step in discovery and development of novel biomarkers. Whole exome sequencing (WES) is a powerful method for the detection of cancer driver mutations. The present work focuses on identifying functionally damaging mutations in patients with high-grade serous ovarian carcinoma (HGSC) through computational analysis of WES. In this study, WES data of HGSC patients was retrieved from the genomic literature available in sequence read archive, the variants were identified and comprehensive structural and functional analysis was performed. Interestingly, I66T and V138I mutations were found to be co-occurring in the IL7R gene in four out of five HGSC patient samples investigated in this study. The V138I mutation was located in the fibronectin type-3 domain and computationally assessed to be causing disruptive effects on the structure and dynamics of IL7R protein. This mutation was found to be co-occurring with the neutral I66T mutation in the same domain which compensated the disruptive effects of V138I variant. These comprehensive studies point to a hitherto unexplored significant role of the IL7R gene in ovarian carcinoma. It is envisaged that the work will lay the foundation for the development of a novel biomarker with potential application in molecular profiling and in estimation of the disease prognosis.Communicated by Ramaswamy H. Sarma.

Immunogenomic intertumor heterogeneity across primary and metastatic sites in a patient with lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer death, partially owing to its extensive heterogeneity. The analysis of intertumor heterogeneity has been limited by an inability to concurrently obtain tissue from synchronous metastases unaltered by multiple prior lines of therapy.

Methods

In order to study the relationship between genomic, epigenomic and T cell repertoire heterogeneity in a rare autopsy case from a 32-year-old female never-smoker with left lung primary late-stage lung adenocarcinoma (LUAD), we did whole-exome sequencing (WES), DNA methylation and T cell receptor (TCR) sequencing to characterize the immunogenomic landscape of one primary and 19 synchronous metastatic tumors.

Results

We observed heterogeneous mutation, methylation, and T cell patterns across distinct metastases. Only TP53 mutation was detected in all tumors suggesting an early event while other cancer gene mutations were later events which may have followed subclonal diversification. A set of prevalent T cell clonotypes were completely excluded from left-side thoracic tumors indicating distinct T cell repertoire profiles between left-side and non left-side thoracic tumors. Though a limited number of predicted neoantigens were shared, these were associated with homology of the T cell repertoire across metastases. Lastly, ratio of methylated neoantigen coding mutations was negatively associated with T-cell density, richness and clonality, suggesting neoantigen methylation may partially drive immunosuppression.

Conclusions

Our study demonstrates heterogeneous genomic and T cell profiles across synchronous metastases and how restriction of unique T cell clonotypes within an individual may differentially shape the genomic and epigenomic landscapes of synchronous lung metastases.

The genomic and immune landscape of long-term survivors of high-grade serous ovarian cancer

Fewer than half of all patients with advanced-stage high-grade serous ovarian cancers (HGSCs) survive more than five years after diagnosis, but those who have an exceptionally long survival could provide insights into tumor biology and therapeutic approaches. We analyzed 60 patients with advanced-stage HGSC who survived more than 10 years after diagnosis using whole-genome sequencing, transcriptome and methylome profiling of their primary tumor samples, comparing this data to 66 short- or moderate-term survivors. Tumors of long-term survivors were more likely to have multiple alterations in genes associated with DNA repair and more frequent somatic variants resulting in an increased predicted neoantigen load. Patients clustered into survival groups based on genomic and immune cell signatures, including three subsets of patients with BRCA1 alterations with distinctly different outcomes. Specific combinations of germline and somatic gene alterations, tumor cell phenotypes and differential immune responses appear to contribute to long-term survival in HGSC.

Modulating the tumor immune microenvironment with nanoparticles: A sword for improving the efficiency of ovarian cancer immunotherapy

With encouraging antitumor effects, immunotherapy represented by immune checkpoint blockade has developed into a mainstream cancer therapeutic modality. However, only a minority of ovarian cancer (OC) patients could benefit from immunotherapy. The main reason is that most OC harbor a suppressive tumor immune microenvironment (TIME). Emerging studies suggest that M2 tumor-associated macrophages (TAMs), T regulatory cells (Tregs), myeloid-derived suppressor cells (MDSCs), and cancer-associated fibroblasts (CAFs) are enriched in OC. Thus, reversing the suppressive TIME is considered an ideal candidate for improving the efficiency of immunotherapy. Nanoparticles encapsulating immunoregulatory agents can regulate immunocytes and improve the TIME to boost the antitumor immune response. In addition, some nanoparticle-mediated photodynamic and photothermal therapy can directly kill tumor cells and induce tumor immunogenic cell death to activate antigen-presenting cells and promote T cell infiltration. These advantages make nanoparticles promising candidates for modulating the TIME and improving OC immunotherapy. In this review, we analyzed the composition and function of the TIME in OC and summarized the current clinical progress of OC immunotherapy. Then, we expounded on the promising advances in nanomaterial-mediated immunotherapy for modulating the TIME in OC. Finally, we discussed the obstacles and challenges in the clinical translation of this novel combination treatment regimen. We believe this resourceful strategy will open the door to effective immunotherapy of OC and benefit numerous patients.

Single-cell analysis of multiple myelomas refines the molecular features of bortezomib treatment responsiveness

Both the tumor and tumor microenvironment (TME) are crucial for pathogenesis and chemotherapy resistance in multiple myeloma (MM). Bortezomib, commonly used for MM treatment, works on both MM and TME cells, but innate and acquired resistance easily develop. By single-cell RNA sequencing (scRNA-seq), we investigated bone marrow aspirates of 18 treatment-naïve MM patients who later received bortezomib-based treatments. Twelve plasma and TME cell types and their subsets were identified. Suboptimal responders (SORs) to bortezomib exhibited higher copy number alteration burdens than optimal responders (ORs). Forty-four differentially expressed genes for SORs based on scRNA-seq data were further analyzed in an independent cohort of 90 treatment-naïve MMs, where 24 genes were validated. A combined model of three clinical variables (older age, low absolute lymphocyte count, and no autologous stem cell transplantation) and 24 genes was associated with bortezomib responsiveness and poor prognosis. In T cells, cytotoxic memory, proliferating, and dysfunctional subsets were significantly enriched in SORs. Moreover, we identified three monocyte subsets associated with bortezomib responsiveness and an MM-specific NK cell trajectory that ended with an MM-specific subset. scRNA-seq predicted the interaction of the GAS6-MERTK, ALCAM-CD6, and BAG6-NCR gene networks. Of note, tumor cells from ORs and SORs were the most prominent sources of ALCAM on effector T cells and BAG6 on NK cells, respectively. Our results indicate that the complicated compositional and molecular changes of both tumor and immune cells in the bone marrow (BM) milieu are important in the development and acquisition of resistance to bortezomib-based treatment of MM.

Integration of local and systemic immunity in ovarian cancer: Implications for immunotherapy

Cancer is a disease that induces many local and systemic changes in immunity. The difficult nature of ovarian cancer stems from the lack of characteristic symptoms that contributes to a delayed diagnosis and treatment. Despite the enormous progress in immunotherapy, its efficacy remains limited. The heterogeneity of tumors, lack of diagnostic biomarkers, and complex immune landscape are the main challenges in the treatment of ovarian cancer. Integrative approaches that combine the tumor microenvironment - local immunity - together with periphery - systemic immunity - are urgently needed to improve the understanding of the disease and the efficacy of treatment. In fact, multiparametric analyses are poised to improve our understanding of ovarian tumor immunology. We outline an integrative approach including local and systemic immunity in ovarian cancer. Understanding the nature of both localized and systemic immune responses will be crucial to boosting the efficacy of immunotherapies in ovarian cancer patients.

Clinical Implications and Molecular Characterization of Drebrin-Positive, Tumor-Infiltrating Exhausted T Cells in Lung Cancer

T cells express an actin-binding protein, drebrin, which is recruited to the contact site between the T cells and antigen-presenting cells during the formation of immunological synapses. However, little is known about the clinical implications of drebrin-expressing, tumor-infiltrating lymphocytes (TILs). To address this issue, we evaluated 34 surgical specimens of pathological stage I-IIIA squamous cell lung cancer. The immune context of primary tumors was investigated using fluorescent multiplex immunohistochemistry. The high-speed scanning of whole-slide images was performed, and the tissue localization of TILs in the tumor cell nest and surrounding stroma was automatically profiled and quantified. Drebrin-expressing T cells were characterized using drebrin⁺ T cells induced in vitro and publicly available single-cell RNA sequence (scRNA-seq) database. Survival analysis using the propensity scores revealed that a high infiltration of drebrin⁺ TILs within the tumor cell nest was independently associated with short relapse-free survival and overall survival. Drebrin⁺ T cells induced in vitro co-expressed multiple exhaustion-associated molecules. The scRNA-seq analyses confirmed that the exhausted tumor-infiltrating CD8⁺ T cells specifically expressed drebrin. Our study suggests that drebrin-expressing T cells present an exhausted phenotype and that tumor-infiltrating drebrin⁺ T cells affect clinical outcomes in patients with resectable squamous cell lung cancer.

Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers

Accumulating evidence has recognized that cancer-associated fibroblasts (CAFs) are major players in the desmoplastic stroma of ovarian cancer, modulating tumor progression and therapeutic response. However, it is unclear regarding the signatures of CAFs could be utilized to predict the clinical outcomes of ovarian cancer patients. To fill in this gap, we explored the intratumoral compartment of ovarian cancer by analyzing the single-cell RNA-sequencing (scRNA-seq) datasets of ovarian carcinoma samples, and identified two distinct CAFs (tumor-promoting CAF_c1 subtype and myofibroblasts-like CAF_c2 subtype). The clinical significance of CAF subtypes was further validated in The Cancer Genomics Atlas (TCGA) database and other independent immunotherapy response datasets, and the results revealed that the patients with a higher expression of CAF_c1 signatures had a worse prognosis and showed a tendency of resistance to immunotherapy. This work uncovered the signatures of the CAF_c1 subtype that could serve as a novel prognostic indicator and predictive marker for immunotherapy.

Immunobiology of high-grade serous ovarian cancer: lessons for clinical translation

Treatment of high-grade serous ovarian cancer (HGSOC) remains challenging. Although HGSOC can potentially be responsive to immunotherapy owing to endogenous immunity at the molecular or T cell level, immunotherapy for this disease has fallen short of expectations to date. This Review proposes a working classification for HGSOC based on the presence or absence of intraepithelial T cells, and elaborates the putative mechanisms that give rise to such immunophenotypes. These differences might explain the failures of existing immunotherapies, and suggest that rational therapeutic approaches tailored to each immunophenotype might meet with improved success. In T cell-inflamed tumours, treatment could focus on mobilizing pre-existing immunity and strengthening the activation of T cells embedded in intraepithelial tumour myeloid niches. Conversely, in immune-excluded and immune-desert tumours, treatment could focus on restoring inflammation by reprogramming myeloid cells, stromal cells and vascular epithelial cells. Poly(ADP-ribose) polymerase (PARP) inhibitors, low-dose radiotherapy, epigenetic drugs and anti-angiogenesis therapy are among the tools available to restore T cell infiltration in HGSOC tumours and could be implemented in combination with vaccines and redirected T cells.

Artificial intelligence and machine learning in cancer imaging

An increasing array of tools is being developed using artificial intelligence (AI) and machine learning (ML) for cancer imaging. The development of an optimal tool requires multidisciplinary engagement to ensure that the appropriate use case is met, as well as to undertake robust development and testing prior to its adoption into healthcare systems. This multidisciplinary review highlights key developments in the field. We discuss the challenges and opportunities of AI and ML in cancer imaging; considerations for the development of algorithms into tools that can be widely used and disseminated; and the development of the ecosystem needed to promote growth of AI and ML in cancer imaging.

A novel subtype to predict prognosis and treatment response with DNA driver methylation-transcription in ovarian cancer

Aims: To identify a novel subtype with DNA driver methylation-transcriptomic multiomics and predict prognosis and therapy response in serous ovarian cancer (SOC). Methods: SOC cohorts with both mRNA and methylation were collected, and DNA driver methylation (DNAme) was identified with the MithSig method. A novel prognostic subtype was developed by integrating the information on DNAme and prognosis-regulated DNAme-associated mRNA by similarity network fusion. Results: 43 overlapped DNAme were identified in three independent cohorts. SOC patients were categorized into three distinct subtypes by integrated multiomics. There were differences in prognosis, tumor microenvironment and response to therapy among the subtypes. Conclusion: This study identified 43 DNAmes and proposes a novel subtype toward personalized chemotherapy and immunotherapy for SOC patients based on multiomics.

Identification of Four Hub Genes as Promising Biomarkers for the Evaluation of Ovarian Cancer Prognosis

Ovarian malignant growth is perhaps the most lethal disease in females. There are no exact biomarkers for the early determination of ovarian disease. We obtained a total of 12 gene clusters through WGCNA and studied the azure gene modules related to the lymphatic infiltration of ovarian cancer further. What’s more, endurance investigation was utilized to decide three qualities connected with the by and large and infection-free endurance in ovarian disease patients, including GOGA8B [Hazard Ratio (HR)=1.53, p=0.037, 95% CI: 1.05–2.24], LRRC26 (HR=0.7, p =0.045, 95% CI: 0.48–1.01), and CCDC114 (HR = 0.72, p = 0.042, 95% CI: 0.53–0.98). A prognostic risk score model was built to anticipate the endurance pace of patients at 1, 3, and 5 years, individually. The area under the receiver operating characteristic (ROC) curve (AUC) of the training set was 0.749, 0.764, and 0.784, respectively; the test AUC was 0.601, 0.623, and 0.709. Our review gives a point of view on significant possible biomarkers for the determination, anticipation, and therapy of ovarian malignant growth.

VSSP abrogates murine ovarian tumor-associated myeloid cell-driven immune suppression and induces M1 polarization in tumor-associated macrophages from ovarian cancer patients

The ovarian tumor microenvironment (TME) is characterized by the accumulation of immunosuppressive tumor-associated macrophages (TAMs) and granulocytic cells. Very small size particles (VSSP), comprised of the ganglioside NAcGM3 and Neisseria meningitidis derived outer membrane vesicles, is being developed as a nanoparticulated modulator of innate immunity. Prior studies have shown that VSSP enhanced antigen-specific cytotoxic T cell responses and reduced the suppressive phenotype of splenic granulocytic cells in tumor-bearing mice. Here, we hypothesized that intraperitoneal VSSP would modify myeloid cell accumulation and phenotypes in the ovarian TME and abrogate suppressor function of TAMs and tumor-associated granulocytic cells. In the ID8 syngeneic model of epithelial ovarian cancer, VSSP reduced peritoneal TAMs and induced M1-like polarization in TAMs. In addition, VSSP stimulated peritoneal inflammation characterized by increased granulocytes and monocytes, including inflammatory monocytic cells. VSSP treatment resulted in peritoneal TAMs and granulocytic cells being less suppressive of ex vivo stimulated CD8+ T cell responses. VSSP alone and combined with anti-PD-1 modestly but significantly prolonged survival in tumor-bearing mice. In addition, ex vivo treatment with VSSP induced M1-like polarization in TAMs from patients with metastatic ovarian cancer and variably abrogated their suppressor phenotype. VSSP treatment also partially abrogated the induction of suppressor function in healthy donor neutrophils exposed to ascites supernatants from patients with ovarian cancer. Together, these results point to VSSP reprogramming myeloid responses resulting in abrogation of suppressive pathways and raise the potential for administration of VSSP into the TME to enhance anti-tumor immunity.

Paving the Way to Solid Tumors: Challenges and Strategies for Adoptively Transferred Transgenic T Cells in the Tumor Microenvironment

T cells are important players in the antitumor immune response. Over the past few years, the adoptive transfer of genetically modified, autologous T cells-specifically redirected toward the tumor by expressing either a T cell receptor (TCR) or a chimeric antigen receptor (CAR)-has been adopted for use in the clinic. At the moment, the therapeutic application of CD19- and, increasingly, BCMA-targeting-engineered CAR-T cells have been approved and have yielded partly impressive results in hematologic malignancies. However, employing transgenic T cells for the treatment of solid tumors remains more troublesome, and numerous hurdles within the highly immunosuppressive tumor microenvironment (TME) need to be overcome to achieve tumor control. In this review, we focused on the challenges that these therapies must face on three different levels: infiltrating the tumor, exerting efficient antitumor activity, and overcoming T cell exhaustion and dysfunction. We aimed to discuss different options to pave the way for potent transgenic T cell-mediated tumor rejection by engineering either the TME or the transgenic T cell itself, which responds to the environment.

Improved T-cell Immunity Following Neoadjuvant Chemotherapy in Ovarian Cancer

PURPOSE

Although local tissue-based immune responses are critical for elucidating direct tumor-immune cell interactions, peripheral immune responses are increasingly recognized as occupying an important role in anticancer immunity. We evaluated serial blood samples from patients with advanced epithelial ovarian cancer (EOC) undergoing standard-of-care neoadjuvant carboplatin and paclitaxel chemotherapy (including dexamethasone for prophylaxis of paclitaxel-associated hypersensitivity reactions) to characterize the evolution of the peripheral immune cell function and composition across the course of therapy.

EXPERIMENTAL DESIGN

Serial blood samples from 10 patients with advanced high-grade serous ovarian cancer treated with neoadjuvant chemotherapy (NACT) were collected before the initiation of chemotherapy, after the third and sixth cycles, and approximately 2 months after completion of chemotherapy. T-cell function was evaluated using ex vivo IFNγ ELISpot assays, and the dynamics of T-cell repertoire and immune cell composition were assessed using bulk and single-cell RNA sequencing (RNAseq).

RESULTS

T cells exhibited an improved response to viral antigens after NACT, which paralleled the decrease in CA125 levels. Single-cell analysis revealed increased numbers of memory T-cell receptor (TCR) clonotypes and increased central memory CD8+ and regulatory T cells throughout chemotherapy. Finally, administration of NACT was associated with increased monocyte frequency and expression of HLA class II and antigen presentation genes; single-cell RNAseq analyses showed that although driven largely by classical monocytes, increased class II gene expression was a feature observed across monocyte subpopulations after chemotherapy.

CONCLUSIONS

NACT may alleviate tumor-associated immunosuppression by reducing tumor burden and may enhance antigen processing and presentation. These findings have implications for the successful combinatorial applications of immune checkpoint blockade and therapeutic vaccine approaches in EOC.

The impact of neoadjuvant chemotherapy on the tumor microenvironment in advanced high-grade serous carcinoma

High-grade serous ovarian, fallopian tube or peritoneal carcinoma is an aggressive subtype of ovarian cancer that frequently develops resistance to chemotherapy. It remains contested whether the resistance is caused by the acquisition of novel molecular aberrations or alternatively through the selection of rare pre-existing tumor clones. To address this question, we applied single-cell RNA sequencing to depict the tumor landscape of 6 samples from a single case of advanced high-grade serous fallopian tube carcinoma during neoadjuvant chemotherapy (NACT). We analyzed a total of 32,079 single cells, with 17,249 cells derived from the pre-NACT multisite tumor tissue samples and 14,830 cells derived from the post-NACT multisite tumor tissue samples. We identified the diverse properties of the tumor, immune and stromal cell types between the pre-NACT and post-NACT tumors. The malignant epithelial cells displayed a high degree of intratumor heterogeneity in response to NACT. We showed that the primary resistant clone (clone 63) epithelial genotype was already present in the pre-NACT tumors, and was adaptively enriched after NACT. This clone 63 was correlated with a poor clinical prognosis. Furthermore, single-cell analysis of CD4⁺ T cells demonstrated that IL2RAhi-CCL22+-Tregs were selectively enriched in post-NACT tumors. Interestingly, this Treg subtype could recruit and enrich themselves through secreting the CCL22-CCR1 combination in pre-NACT and post-NACT tumors, and further express CD274 to suppress other CD4 and CD8 T cells through a CD274-PDCD1 axis in the post-NACT tumors, and this predicted an immunosuppressive state after NACT. Overall, our results provide important evidence for the adaptive resistance theory of HGSC, and for the potential development of therapeutic strategies to treat HGSC and improve the survival of patients with HGSC.

Organ-specific efficacy in advanced non-small cell lung cancer patients treated with first-line single-agent immune checkpoint inhibitors

Background:

Methods:

Results:

Conclusions:

Identification of Malignant Cell Populations Associated with Poor Prognosis in High-Grade Serous Ovarian Cancer Using Single-Cell RNA Sequencing

Simple Summary

Ovarian cancer has a high recurrence rate (~75%), and tumor heterogeneity is associated with such tumor recurrence. However, it is still poorly understood in ovarian cancer. To reveal tumor heterogeneity, we performed single-cell RNA sequencing (RNA-seq) of serous ovarian cancer cells from four different patients: two with primary carcinoma, one with recurrent carcinoma, and one with carcinoma treated with interval debulking surgery. As a result, we found two malignant tumor cell subtypes associated with poor prognosis. One malignant population included the earliest cancer cells and cancer stem-like cells. SLC3A1 and PEG10 were identified as the marker genes of cancer-initiating cells. The other malignant population expressing CA125 (MUC16), the most common biomarker for ovarian cancer, is associated with a decrease in the number of tumor-infiltrating cytotoxic T lymphocytes (CTLs). Our findings will offer new markers for diagnosis and choosing treatments targeting the malignant populations in ovarian cancer.

Abstract

To reveal tumor heterogeneity in ovarian cancer, we performed single-cell RNA sequencing (RNA-seq). We obtained The Cancer Genome Atlas (TCGA) survival data and TCGA gene expression data for a Kaplan–Meier plot showing the association of each tumor population with poor prognosis. As a result, we found two malignant tumor cell subtypes associated with poor prognosis. Next, we performed trajectory analysis using scVelo and Monocle3 and cell–cell interaction analysis using CellphoneDB. We found that one malignant population included the earliest cancer cells and cancer stem-like cells. Furthermore, we identified SLC3A1 and PEG10 as the marker genes of cancer-initiating cells. The other malignant population expressing CA125 (MUC16) is associated with a decrease in the number of tumor-infiltrating cytotoxic T lymphocytes (CTLs). Moreover, cell–cell interaction analysis implied that interactions mediated by LGALS9 and GAS6, expressed by this malignant population, caused the CTL suppression. The results of this study suggest that two tumor cell populations, including a cancer-initiating cell population and a population expressing CA125, survive the initial treatment and suppress antitumor immunity, respectively, and are associated with poor prognosis. Our findings offer a new understanding of ovarian cancer heterogeneity and will aid in the development of diagnostic tools and treatments.

The presence and size of intrahepatic tumors determine the therapeutic efficacy of nivolumab in advanced hepatocellular carcinoma

Purpose:

Inter-tumoral heterogeneity at the differential lesion level raises the possibility of distinct organ-specific responses to immune checkpoint inhibitors (ICIs). We aimed to comprehensively examine the clinicopathological factors to predict and assess the efficacy of nivolumab, programmed cell death protein 1 (PD-1) blockade at an individual tumor site-specific level in patients with advanced hepatocellular carcinoma (aHCC).

Patients and Methods:

We enrolled 261 aHCC patients treated with nivolumab between 2012 and 2018. Eighty-one clinicopathological factors were comprehensively collected and analyzed. The association between all variables and survival outcomes was evaluated. According to tumor site, the organ-specific responses were assessed based on the Response Evaluation Criteria in Solid Tumors, version 1.1.

Results:

The liver was the most commonly involved organ (75.1%), followed by the lungs (37.5%) and lymph nodes (LNs, 11.5%). The liver of nonresponders was more frequently the organ of progression, while the lungs of responders were more frequently the organs of response. Among the 455 individual lesions (liver, n = 248; lung, n = 124; LN, n = 35; others including bone or soft tissues, n = 48), intrahepatic tumors showed the least response (10.1%), followed by lung (24.2%) and LN tumors (37.1%), indicating the presence of distinct organ-specific responses to nivolumab. In intrahepatic tumors, the organ-specific response rate decreased as the size increased (13% for ⩽50 mm, 8.1% for 50–100 mm, and 5.5% for >100 mm). In the subgroup analysis according to tumor location, patients with lung only metastasis (⩾30 mm) showed the best progression-free survival (PFS) and overall survival (OS). In contrast, primary HCC (⩾100 mm) without lung metastasis had the worst PFS and OS. Comprehensive analyses also revealed that liver function and systemic inflammatory indices, such as neutrophil-to-lymphocyte ratio (NLR), were significantly associated with PFS and OS.

Conclusion:

The presence and size of liver tumors, liver function, and NLR are key factors determining the response to nivolumab in aHCC. These clinical factors should be considered when treating patients with advanced HCC with PD-1 blockade.

Macrophage-derived CCL23 upregulates expression of T-cell exhaustion markers in ovarian cancer

BACKGROUND

Macrophages are an important component of the tumour immune microenvironment (TME) and can promote tumour growth and metastasis. Macrophage-secreted chemokine-ligand-23 (CCL23) induces ovarian cancer cell migration via chemokine-receptor 1 (CCR1). However, the effect of CCL23 on other immune cells in the TME is unknown.

METHODS

CCL23 levels were measured by ELISA. The expression of surface markers in exhaustion assays was quantified by flow cytometry. Signalling pathways were identified by phosphokinase array and validated by western blot.

RESULTS

Ascites from patients with high-grade serous ovarian cancer (HGSC) contain high levels of CCL23. Similarly, significantly higher CCL23 levels were found in plasma from HGSC patients compared to healthy individuals. RNA-seq analysis of ovarian cancer tissues from TCGA showed that expression of CCL23 correlated with the presence of macrophages. In tissues with high levels of CCL23 and macrophage content, the fraction of CD8 + T cells expressing exhaustion markers CTLA-4 and PD-1 were significantly higher compared to low-level CCL23 tissues. In vitro, CCL23 induced upregulation of immune checkpoint proteins on CD8 + T cells, including CTLA-4, TIGIT, TIM-3 and LAG-3 via phosphorylation of GSK3β in CD8 + T cells.

CONCLUSIONS

Our data suggest that CCL23 produced by macrophages contributes to the immune-suppressive TME in ovarian cancer by inducing an exhausted T-cell phenotype.

Neoantigen quality predicts immunoediting in survivors of pancreatic cancer

Cancer immunoediting¹ is a hallmark of cancer² that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice^1,3, whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features—‘non-selfness’  based on neoantigen similarity to known antigens^4,5, and ‘selfness’  based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer.

The human immune system naturally edits cancers of high-quality neoantigens.

Cancer evolution: special focus on the immune aspect of cancer

Cancer is an evolutionary disease. Intra-tumor heterogeneity (ITH), which describes the diversity within individual tumors, sets the foundation for evolution. The fitness of tumor cells is determined by their microenvironment, which exerts intense selection pressure that generally favors cells with survival and proliferation advantages. It has been revealed that host immunity dramatically influences the evolutionary trajectory of cancer. As technologies advance, a refined map of the immune system's involvement in cancer evolution has gradually come to our knowledge. Here we specifically view cancer through the lens of evolutionary immunological biology. We will cover the neoplastic evolution under immunosurveillance, including how the host immunity shapes the tumor evolutionary trajectory and how progressive tumors modulate the host immunity to survive. A comprehensive understanding of the interplay between cancer evolution and cancer immunity provides clues to combating cancer strategically.

Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis

Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS is widely used in the diagnosis and treatment of various diseases, including cancer. Over the years, SCS has gradually become an effective clinical tool for the exploration of tumor metastasis mechanisms and the development of treatment strategies. Currently, SCS can be used not only to analyze metastasis-related malignant biological characteristics, such as tumor heterogeneity, drug resistance, and microenvironment, but also to construct metastasis-related cell maps for predicting and monitoring the dynamics of metastasis. SCS is also used to identify therapeutic targets related to metastasis as it provides insights into the distribution of tumor cell subsets and gene expression differences between primary and metastatic tumors. Additionally, SCS techniques in combination with artificial intelligence (AI) are used in liquid biopsy to identify circulating tumor cells (CTCs), thereby providing a novel strategy for treating tumor metastasis. In this review, we summarize the potential applications of SCS in the field of tumor metastasis and discuss the prospects and limitations of SCS to provide a theoretical basis for finding therapeutic targets and mechanisms of metastasis.

A Selective β-Catenin-Metadherin/CEACAM1-CCL3 Axis Mediates Metastatic Heterogeneity upon Tumor-Macrophage Interaction

Tumor heterogeneity plays a key role in cancer relapse and metastasis, however, the distinct cellular behaviors and kinetics of interactions among different cancer cell subclones and the tumor microenvironment are poorly understood. By profiling an isogenic model that resembles spontaneous human ovarian cancer metastasis with an highly metastatic (HM) and non-metastatic (NM) tumor cell pair, one finds an upregulation of Wnt/β-catenin signaling uniquely in HM. Using humanized immunocompetent mice, one shows for the first time that activated β-catenin acts nonautonomously to modulate the immune microenvironment by enhancing infiltrating tumor-associated macrophages (TAM) at the metastatic site. Single-cell time-lapse microscopy further reveals that upon contact with macrophages, a significant subset of HM, but not NM, becomes polyploid, a phenotype pivotal for tumor aggressiveness and therapy resistance. Moreover, HM, but not NM, polarizes macrophages to a TAM phenotype. Mechanistically, β-catenin upregulates cancer cell surface metadherin, which communicates through CEACAM1 expressed on macrophages to produce CCL3. Tumor xenografts in humanized mice and clinical patient samples both corroborate the relevance of enhanced metastasis, TAM activation, and polyploidy in vivo. The results thus suggest that targeting the β-catenin-metadherin/CEACAM1-CCL3 positive feedback cascade holds great therapeutic potential to disrupt polyploidization of the cancer subclones that drive metastasis.

Paired primary and metastatic lesions of patients with ipilimumab-treated melanoma: high variation in lymphocyte infiltration and HLA-ABC expression whereas tumor mutational load is similar and correlates with clinical outcome

BACKGROUND

Immune checkpoint inhibitors (ICI) can lead to long-term responses in patients with metastatic melanoma. Still many patients with melanoma are intrinsically resistant or acquire secondary resistance. Previous studies have used primary or metastatic tumor tissue for biomarker assessment. Especially in melanoma, metastatic lesions are often present at different anatomical sites such as skin, lymph nodes, and visceral organs. The anatomical site may directly affect the tumor microenvironment (TME). To evaluate the impact of tumor evolution on the TME and on ICI treatment outcome, we directly compared paired primary and metastatic melanoma lesions for tumor mutational burden (TMB), HLA-ABC status, and tumor infiltrating lymphocytes (TILs) of patients that received ipilimumab.

METHODS

TMB was analyzed by sequencing primary and metastatic melanoma lesions using the TruSight Oncology 500 assay. Tumor tissues were subjected to multiplex immunohistochemistry to assess HLA-ABC status and for the detection of TIL subsets (B cells, cytotoxic T cells, helper T cells, and regulatory T cells), by using a machine-learning algorithm.

RESULTS

While we observed a very good agreement between TMB of matched primary and metastatic melanoma lesions (intraclass coefficient=0.921), such association was absent for HLA-ABC status, TIL density, and subsets thereof. Interestingly, analyses of different metastatic melanoma lesions within a single patient revealed that TIL density and composition agreed remarkably well, rejecting the hypothesis that the TME of different anatomical sites affects TIL infiltration. Similarly, the HLA-ABC status between different metastatic lesions within patients was also comparable. Furthermore, high TMB, of either primary or metastatic melanoma tissue, directly correlated with response to ipilimumab, whereas lymphocyte density or composition did not. Loss of HLA-ABC in the metastatic lesion correlated to a shorter progression-free survival on ipilimumab.

CONCLUSIONS

We confirm the link between TMB and HLA-ABC status and the response to ipilimumab-based immunotherapy in melanoma, but no correlation was found for TIL density, neither in primary nor metastatic lesions. Our finding that TMB between paired primary and metastatic melanoma lesions is highly stable, demonstrates its independency of the time point and location of acquisition. TIL and HLA-ABC status in metastatic lesions of different anatomical sites are highly similar within an individual patient.

A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts Tumor Immune Profiles in Non-Small Cell Lung Cancer: A Retrospective Multicohort Study

Background

The tumor immune microenvironment (TIME) phenotypes have been reported to mainly impact the efficacy of immunotherapy. Given the increasing use of immunotherapy in cancers, knowing an individual's TIME phenotypes could be helpful in screening patients who are more likely to respond to immunotherapy. Our study intended to establish, validate, and apply a machine learning model to predict TIME profiles in non-small cell lung cancer (NSCLC) by using 18F-FDG PET/CT radiomics and clinical characteristics.

Methods

The RNA-seq data of 1145 NSCLC patients from The Cancer Genome Atlas (TCGA) cohort were analyzed. Then, 221 NSCLC patients from Daping Hospital (DPH) cohort received18F-FDG PET/CT scans before treatment and CD8 expression of the tumor samples were tested. The Artificial Intelligence Kit software was used to extract radiomic features of PET/CT images and develop a radiomics signature. The models were established by radiomics, clinical features, and radiomics-clinical combination, respectively, the performance of which was calculated by receiver operating curves (ROCs) and compared by DeLong test. Moreover, based on radiomics score (Rad-score) and clinical features, a nomogram was established. Finally, we applied the combined model to evaluate TIME phenotypes of NSCLC patients in The Cancer Imaging Archive (TCIA) cohort (n = 39).

Results

TCGA data showed CD8 expression could represent the TIME profiles in NSCLC. In DPH cohort, PET/CT radiomics model outperformed CT model (AUC: 0.907 vs. 0.861, P = 0.0314) to predict CD8 expression. Further, PET/CT radiomics-clinical combined model (AUC = 0.932) outperformed PET/CT radiomics model (AUC = 0.907, P = 0.0326) or clinical model (AUC = 0.868, P = 0.0036) to predict CD8 expression. In the TCIA cohort, the predicted CD8-high group had significantly higher immune scores and more activated immune pathways than the predicted CD8-low group (P = 0.0421).

Conclusion

Our study indicates that 18F-FDG PET/CT radiomics-clinical combined model could be a clinically practical method to non-invasively detect the tumor immune status in NSCLCs.

The Cellular Tumor Immune Microenvironment of Childhood Solid Cancers: Informing More Effective Immunotherapies

Common pediatric solid cancers fail to respond to standard immuno-oncology agents relying on preexisting adaptive antitumor immune responses. The adoptive transfer of tumor-antigen specific T cells, such as CAR-gene modified T cells, is an attractive strategy, but its efficacy has been limited. Evidence is accumulating that local barriers in the tumor microenvironment prevent the infiltration of T cells and impede therapeutic immune responses. A thorough understanding of the components of the functional compartment of the tumor microenvironment and their interaction could inform effective combination therapies and novel engineered therapeutics, driving immunotherapy towards its full potential in pediatric patients. This review summarizes current knowledge on the cellular composition and significance of the tumor microenvironment in common extracranial solid cancers of childhood and adolescence, such as embryonal tumors and bone and soft tissue sarcomas, with a focus on myeloid cell populations that are often present in abundance in these tumors. Strategies to (co)target immunosuppressive myeloid cell populations with pharmacological anticancer agents and with selective antagonists are presented, as well as novel concepts aiming to employ myeloid cells to cooperate with antitumor T cell responses.

Mechanism of Phellodendron and Anemarrhena Drug Pair on the Treatment of Liver Cancer Based on Network Pharmacology and Bioinformatics

Background

This study aims to explore the key targets and signaling pathways of the traditional Chinese medicine Phellodendron and Anemarrhena drug pair (PADP) for the treatment of liver cancer.

Methods

Firstly, bioinformatics technology was used to analyze GSE62232 gene chip to obtain the differential genes of liver cancer. A network pharmacology technology was used to find the active components of PADP and their targets. Secondly, the differential genes were imported into STRING database to draw a PPI network, and network topology structure map combined with Cytoscape software. And the R language was used to identify differential gene targets and pathways through GO and KEGG pathway enrichment analysis. In addition, AutoDock Vina was used for molecular docking of core targets and core compounds. Moreover, GEPIA online analysis tool was used to perform survival analysis of the core target genes. Finally, RT-PCR was used to verify the changes of key target genes. CCK−8 assay was performed to detect cell proliferation. Flow cytometry was performed to detect the cell cycle and apoptotic. Transwell invasion assay was performed to detect cell invasion.

Results

Firstly, a total of 21,654 genes were obtained. After screening, 1019 differential genes were obtained, including 614 down-regulated genes and 405 up-regulated genes. Furthermore, after screening by ADME standards, 52 active ingredients were obtained, of which 37 were Phellodendron and 15 were Anemarrhena. And a total of 36 differential genes have been identified, including 13 up-regulated genes and 23 down-regulated genes. Moreover, through enrichment analysis, we found that PADP may treat liver cancer through multiple channels and multiple pathways including the p53 signaling pathway, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway and so on. Secondly, the molecular docking results showed that there was certain affinity between the core compounds and core target genes. In addition, GEPIA online analysis showed that ESR1, AR, CCNB1, CDK1, AKR1C3 and CCNA2 might become potential target genes for the survival and prognosis of PADP for the treatment of liver cancer. Finally, it was found that PADP could up regulate genes ESR1 and AR, down regulate genes CCNB1, CDK1, AKR1C3, and CCNA2. PADP could promote the apoptosis of liver cancer cells, shorten the cell cycle, and inhibit the proliferation and invasion of liver cancer cells.

Conclusion

PADP may treat liver cancer through multiple targets, multiple channels, and multiple pathways, thereby suppressing cancer cells and improving the living quality of patients.

Heterogeneity of the tumor immune microenvironment and its clinical relevance

During the course of tumorigenesis and subsequent metastasis, malignant cells gradually diversify and become more heterogeneous. Consequently, the tumor mass might be infiltrated by diverse immune-related components, including the cytokine/chemokine environment, cytotoxic activity, or immunosuppressive elements. This immunological heterogeneity is universally presented spatially or varies temporally along with tumor evolution or therapeutic intervention across almost all solid tumors. The heterogeneity of anti-tumor immunity shows a profound association with the progression of disease and responsiveness to treatment, particularly in the realm of immunotherapy. Therefore, an accurate understanding of tumor immunological heterogeneity is essential for the development of effective therapies. Facilitated by multi-regional and -omics sequencing, single cell sequencing, and longitudinal liquid biopsy approaches, recent studies have demonstrated the potential to investigate the complexity of immunological heterogeneity of the tumors and its clinical relevance in immunotherapy. Here, we aimed to review the mechanism underlying the heterogeneity of the immune microenvironment. We also explored how clinical assessments of tumor heterogeneity might facilitate the development of more effective personalized therapies.

Integrated immunogenomic analysis of single-cell and bulk tissue transcriptome profiling unravels a macrophage activation paradigm associated with immunologically and clinically distinct behaviors in ovarian cancer

INTRODUCTION

Increasing evidence demonstrates that the activation states and diverse spectrum of macrophage subtypes display dynamic heterogeneity in the tumor microenvironment, which plays a critical role in a variety of cancer types.

OBJECTIVES

To investigate the heterogeneity and the homeostasis of different macrophage subtypes, as well as their effect on biological and clinical manifestations of ovarian cancer (OV).

METHOD

Integrated immunogenomic analysis of single-cell and bulk tissuetranscriptome profiling was performed to systematically investigate the association between macrophage activation and prognostic and therapeutic efficacy. Consensus clustering analysis was used to define novel macrophage subtypes. An artificial neural network was used to simulate the dynamic activation of macrophages.

RESULTS

The pan-cohort results suggested that high relative infiltration abundance of M0 and M1 macrophages was associated with improved outcome and therapeutic efficacy. However, it was the opposite for M2 macrophages. Unsupervised consensus clustering analysis revealed two OV subgroups characterized by a balance between M0, M1 and M2 macrophages with distinct clinical and immunological behaviors. Finally, a macrophage polarization-derived artificial neural network model was proposed to serve as a robust prognostic factor and predictive biomarker for therapeutic efficacy, which was validated in different independent patient cohorts.

CONCLUSION

The present study provides a new understanding of macrophage heterogeneity and its association with OV prognosis and underlines the future clinical potential of a macrophage activation model for tumor prevention and treatment.

The STING pathway: Therapeutic vulnerabilities in ovarian cancer

Ovarian cancer is the leading cause of mortality due to gynecologic malignancy. The majority of women diagnosed with the most common subtype, high-grade serous ovarian carcinoma (HGSC), develop resistance to conventional therapies despite initial response to treatment. HGSC tumors displaying DNA damage repair (DDR) gene deficiency and high chromosomal instability mainly associate with higher cytotoxic immune cell infiltration and expression of genes associated with these immune pathways. Despite the high level of immune infiltration observed, the majority of patients with HGSC have not benefited from immunomodulatory treatments as the mechanistic basis of this infiltration is unclear. This lack of response can be primarily attributed to heterogeneity at the levels of both cancer cell genetic alterations and the tumour immune microenvironment. Strategies to enhance anti-tumour immunity have been investigated in ovarian cancer, of which interferon activating therapies present as an attractive option. Of the several type I interferon (IFN-1) stimulating therapies, exogenously activating the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway is emerging as a promising avenue. Herein, we highlight our current understanding of how constitutive and induced cGAS-STING pathway activation influences the ovarian tumour microenvironment. We further elaborate on the links between the genomic alterations prevalent in ovarian tumours and how the resultant immune phenotypes can make them more susceptible to exogenous STING pathway activation and potentiate immune-mediated killing of cancer cells. The therapeutic potential of cGAS-STING pathway activation in ovarian cancer and factors implicating treatment outcomes are discussed, providing a rationale for future combinatorial treatment approaches on the backbone of chemotherapy.

Identification of neoantigens for individualized therapeutic cancer vaccines

Somatic mutations in cancer cells can generate tumour-specific neoepitopes, which are recognized by autologous T cells in the host. As neoepitopes are not subject to central immune tolerance and are not expressed in healthy tissues, they are attractive targets for therapeutic cancer vaccines. Because the vast majority of cancer mutations are unique to the individual patient, harnessing the full potential of this rich source of targets requires individualized treatment approaches. Many computational algorithms and machine-learning tools have been developed to identify mutations in sequence data, to prioritize those that are more likely to be recognized by T cells and to design tailored vaccines for every patient. In this Review, we fill the gaps between the understanding of basic mechanisms of T cell recognition of neoantigens and the computational approaches for discovery of somatic mutations and neoantigen prediction for cancer immunotherapy. We present a new classification of neoantigens, distinguishing between guarding, restrained and ignored neoantigens, based on how they confer proficient antitumour immunity in a given clinical context. Such context-based differentiation will contribute to a framework that connects neoantigen biology to the clinical setting and medical peculiarities of cancer, and will enable future neoantigen-based therapies to provide greater clinical benefit.

CXCL9 inhibits tumour growth and drives anti-PD-L1 therapy in ovarian cancer

Background

Response to immune checkpoint blockade (ICB) in ovarian cancer remains disappointing. Several studies have identified the chemokine CXCL9 as a robust prognosticator of improved survival in ovarian cancer and a characteristic of the immunoreactive subtype, which predicts ICB response. However, the function of CXCL9 in ovarian cancer has been poorly studied.

Methods

Impact of Cxcl9 overexpression in the murine ID8-Trp53^−/− and ID8-Trp53^−/–Brca2^−/− ovarian cancer models on survival, cellular immune composition, PD-L1 expression and anti-PD-L1 therapy. CXCL9 expression analysis in ovarian cancer subtypes and correlation to reported ICB response.

Results

CXCL9 overexpression resulted in T-cell accumulation, delayed ascites formation and improved survival, which was dependent on adaptive immune function. In the ICB-resistant mouse model, the chemokine was sufficient to enable a successful anti-PD-L1 therapy. In contrast, these effects were abrogated in Brca2-deficient tumours, most likely due to an already high intrinsic chemokine expression. Finally, in ovarian cancer patients, the clear-cell subtype, known to respond best to ICB, displayed a significantly higher proportion of CXCL9^high tumours than the other subtypes.

Conclusions

CXCL9 is a driver of successful ICB in preclinical ovarian cancer. Besides being a feasible predictive biomarker, CXCL9-inducing agents thus represent attractive combination partners to improve ICB in this cancer entity.

N6-methyladenosine (m6A) RNA modification in tumor immunity

Growing evidence supports that cancer progression is closely associated with the tumor microenvironment and immune evasion. Importantly, recent studies have revealed the crucial roles of epigenetic regulators in shaping the tumor microenvironment and restoring immune recognition. N6-methyladenosine (m6A) modification, the most prevalent epigenetic modification of mammalian mRNAs, has essential functions in regulating the processing and metabolism of its targeted RNAs, and therefore affects various biological processes including tumorigenesis and progression. Recent studies have demonstrated the critical functions and molecular mechanisms underlying abnormal m6A modification in the regulation of tumor immunity. In this review, we summarize recent research progress in the potential roles of m6A modification in tumor immunoregulation, with a special focus on the anti-tumor processes of immune cells and involvement in immune-associated molecules and pathways. Furthermore, we review current knowledge regarding the close correlation between m6A-related risk signatures and the tumor immune microenvironment landscape, and we discuss the prognostic value and therapeutic efficacy of m6A regulators in a variety of cancer types.

Identification of Neoantigens in Cancer Cells as Targets for Immunotherapy

The clinical benefits of immune checkpoint blockage (ICB) therapy have been widely reported. In patients with cancer, researchers have demonstrated the clinical potential of antitumor cytotoxic T cells that can be reinvigorated or enhanced by ICB. Compared to self-antigens, neoantigens derived from tumor somatic mutations are believed to be ideal immune targets in tumors. Candidate tumor neoantigens can be identified through immunogenomic or immunopeptidomic approaches. Identification of neoantigens has revealed several points of the clinical relevance. For instance, tumor mutation burden (TMB) may be an indicator of immunotherapy. In various cancers, mutation rates accompanying neoantigen loads may be indicative of immunotherapy. Furthermore, mismatch repair-deficient tumors can be eradicated by T cells in ICB treatment. Hence, immunotherapies using vaccines or adoptive T-cell transfer targeting neoantigens are potential innovative strategies. However, significant efforts are required to identify the optimal epitopes. In this review, we summarize the recent progress in the identification of neoantigens and discussed preclinical and clinical studies based on neoantigens. We also discuss the issues remaining to be addressed before clinical applications of these new therapeutic strategies can be materialized.

Integrated molecular profiling of patient-derived ovarian cancer models identifies clinically relevant signatures and tumor vulnerabilities

High‐grade serous ovarian carcinoma (HGSOC) is a highly aggressive and intractable neoplasm, mainly because of its rapid dissemination into the abdominal cavity, a process that is favored by tumor‐associated peritoneal ascites. The precise molecular alterations involved in HGSOC onset and progression remain largely unknown due to the high biological and genetic heterogeneity of this tumor. We established a set of different tumor samples (termed the As11‐set) derived from a single HGSOC patient, consisting of peritoneal ascites, primary tumor cells, ovarian cancer stem cells (OCSC) and serially propagated tumor xenografts. The As11‐set was subjected to an integrated RNA‐seq and DNA‐seq analysis which unveiled molecular alterations that marked the different types of samples. Our profiling strategy yielded a panel of signatures relevant in HGSOC and in OCSC biology. When such signatures were used to interrogate the TCGA dataset from HGSOC patients, they exhibited prognostic and predictive power. The molecular alterations also identified potential vulnerabilities associated with OCSC, which were then tested functionally in stemness‐related assays. As a proof of concept, we defined PI3K signaling as a novel druggable target in OCSC.

Immune subtypes and neoantigen-related immune evasion in advanced colorectal cancer

Elimination of cancerous cells by the immune system is an important mechanism of protection from cancer, however, its effectiveness can be reduced owing to development of resistance and evasion. To understand the systemic immune response in advanced untreated primary colorectal cancer, we analyze immune subtypes and immune evasion via neoantigen-related mechanisms. We identify a distinctive cancer subtype characterized by immune evasion and very poor overall survival. This subtype has less clonal highly expressed neoantigens and high chromosomal instability, resulting in adaptive immune resistance mediated by the immune checkpoint molecules and neoantigen presentation disorders. We also observe that neoantigen depletion caused by immunoediting and high clonal neoantigen load are correlated with a good overall survival. Our results indicate that the status of the tumor microenvironment and neoantigen composition are promising new prognostic biomarkers with potential relevance for treatment plan decisions in advanced CRC.

Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients

Metastatic progression is the main cause of death in cancer patients, whereas the underlying genomic mechanisms driving metastasis remain largely unknown. Here, we assembled MSK-MET, a pan-cancer cohort of over 25,000 patients with metastatic diseases. By analyzing genomic and clinical data from this cohort, we identified associations between genomic alterations and patterns of metastatic dissemination across 50 tumor types. We found that chromosomal instability is strongly correlated with metastatic burden in some tumor types, including prostate adenocarcinoma, lung adenocarcinoma, and HR+/HER2+ breast ductal carcinoma, but not in others, including colorectal cancer and high-grade serous ovarian cancer, where copy-number alteration patterns may be established early in tumor development. We also identified somatic alterations associated with metastatic burden and specific target organs. Our data offer a valuable resource for the investigation of the biological basis for metastatic spread and highlight the complex role of chromosomal instability in cancer progression.

Computational image features of immune architecture is associated with clinical benefit and survival in gynecological cancers across treatment modalities

BACKGROUND

We present a computational approach (ArcTIL) for quantitative characterization of the architecture of tumor-infiltrating lymphocytes (TILs) and their interplay with cancer cells from digitized H&E-stained histology whole slide images and evaluate its prognostic role in three different gynecological cancer (GC) types and across three different treatment types (platinum, radiation and immunotherapy).

METHODS

In this retrospective study, we included 926 patients with GC diagnosed with ovarian cancer (OC), cervical cancer, and endometrial cancer with available digitized diagnostic histology slides and survival outcome information. ArcTIL features quantifying architecture and spatial interplay between immune cells and the rest of nucleated cells (mostly comprised cancer cells) were extracted from the cell cluster graphs of nuclei within the tumor epithelial nests, surrounding stroma and invasive tumor front compartments on H&E-stained slides. A Cox proportional hazards model, incorporating ArcTIL features was fit on the OC training cohort (N=51), yielding an ArcTIL signature. A unique threshold learned from the training set stratified the patients into a low and high-risk group.

RESULTS

The seven feature ArcTIL classifier was found to significantly correlate with overall survival in chemotherapy and radiotherapy-treated validation cohorts and progression-free survival in an immunotherapy-treated validation cohort. ArcTIL features relating to increased density of TILs in the epithelium and invasive tumor front were found to be associated with better survival outcomes when compared with those patients with an increased TIL density in the stroma. A statistically significant association was found between the ArcTIL signature and signaling pathways for blood vessel morphogenesis, vasculature development, regulation of cell differentiation, cell-substrate adhesion, biological adhesion, regulation of vasculature development, and angiogenesis.

CONCLUSIONS

This study reveals that computationally-derived features from the spatial architecture of TILs and tumor cells are prognostic in GCs treated with chemotherapy, radiotherapy, and checkpoint blockade and are closely associated with central biological processes that impact tumor progression. These findings could aid in identifying therapy-refractory patients and further enable personalized treatment decision-making.

Heterogeneity of programmed death-ligand 1 expression and infiltrating lymphocytes in paired resected primary and metastatic non-small cell lung cancer

Metastatic tumors (MTs) may show different characteristics of the immune microenvironment from primary tumors (PTs) in non-small cell lung cancer (NSCLC). The heterogeneity of immune markers in metastatic NSCLC and its associated factors has not been well demonstrated. In this study, 64 surgically resected specimens of paired PTs and MTs were obtained from 28 patients with NSCLC. Multiplex immunofluorescence (mIF; panel including programmed death-ligand 1 (PD-L1), Cytokeratin, CD8, and CD68) was performed on whole sections. The heterogeneity of the immune contexture of PD-L1 expression, infiltrating lymphocytes, and immune-to-tumor cell distances was quantified via digital image analysis. In a quantitative comparison of MTs and corresponding PTs, MTs showed higher PD-L1 expression levels, lower density of CD8+ cytotoxic T lymphocytes (CTLs), and longer spatial distance between CTLs and tumor cells. Subgroup analysis, which associated clinical factors, revealed that the heterogeneity of immune markers was more obvious in extrapulmonary, metachronous, and treated MTs, while fewer differences were observed in intrapulmonary, synchronous, and untreated MTs. In particular, MTs showed significantly higher PD-L1 expression and lower lymphocyte infiltration in metastatic NSCLC with EGFR mutations. Prognosis analysis showed that an increased density of CD8+ CTLs in MTs was associated with better overall survival (OS). Therefore, significant discrepancies in PD-L1 expression and lymphocyte infiltration in metastatic NSCLC are most likely associated with temporal heterogeneity with a history of anti-treatment and correlated with EGFR mutations. The detection of immune markers in re-obtained metastatic specimens may be required for immunotherapy prediction in these patients with metastatic NSCLC.

Back to the Future: Spatiotemporal Determinants of NK Cell Antitumor Function

NK cells play a crucial role in host protection during tumorigenesis. Throughout tumor development, however, NK cells become progressively dysfunctional through a combination of dynamic tissue-specific and systemic factors. While a number of immunosuppressive mechanisms present within the tumor microenvironment have been characterized, few studies have contextualized the spatiotemporal dynamics of these mechanisms during disease progression and across anatomical sites. Understanding how NK cell immunosuppression evolves in these contexts will be necessary to optimize NK cell therapy for solid and metastatic cancers. Here, we outline the spatiotemporal determinants of antitumor NK cell regulation, including heterogeneous tumor architecture, temporal disease states, diverse cellular communities, as well as the complex changes in NK cell states produced by the sum of these higher-order elements. Understanding of the signals encountered by NK cells across time and space may reveal new therapeutic targets to harness the full potential of NK cell therapy for cancer.

Genomic, Immunological, and Clinical Characterization of Pyroptosis in Ovarian Cancer

Purpose

Pyroptosis is a form of lytic programmed cell death that is associated with the pathogenesis of many tumors. However, the potential roles of pyroptosis-related genes (PRGs) in the tumor microenvironment (TME) remain unclear.

Materials and Methods

We systematically described the genetic and transcriptional alterations in PRGs in gynecological cancers. An unsupervised clustering method was used to investigate the molecular subtypes of ovarian cancer (OV) and systematically analyze the TME cell infiltration characteristics. A prognostic signature and nomogram were established to quantify the pyroptosis patterns of individual tumors. We also analyzed the expression levels of eight PRGs in the OV tissues.

Results

Two distinct molecular subtypes of OV were identified, and these two distinct molecular subtypes could predict clinicopathological features, prognosis, TME stromal activity, immune infiltrating cells, and immune checkpoints. A prognostic signature was established, and its predictive capability was validated. Low risk score, characterized by activation of immunity, upregulation of programmed death-ligand 1 expression, lower tumor immune dysfunction and exclusion scores, lower tumor mutation burden, and favorable prognosis. These findings suggested that low-risk patients with OV may be more sensitive to immunotherapy. In addition, this signature could effectively predict the response to chemotherapy in patients with OV. Furthermore, a prognostic nomogram was generated, which exhibited superior predictive accuracy.

Conclusion

This study highlights the crucial role of PRGs in the TME and may help develop immunotherapies and promote individualized therapeutic strategies for patients with OV.

Whole-body CD8+ T cell visualization before and during cancer immunotherapy: a phase 1/2 trial

Immune checkpoint inhibitors (ICIs), by reinvigorating CD8⁺ T cell mediated immunity, have revolutionized cancer therapy. Yet, the systemic CD8⁺ T cell distribution, a potential biomarker of ICI response, remains poorly characterized. We assessed safety, imaging dose and timing, pharmacokinetics and immunogenicity of zirconium-89-labeled, CD8-specific, one-armed antibody positron emission tomography tracer ⁸⁹ZED88082A in patients with solid tumors before and ~30 days after starting ICI therapy (NCT04029181). No tracer-related side effects occurred. Positron emission tomography imaging with 10 mg antibody revealed ⁸⁹ZED88082A uptake in normal lymphoid tissues, and tumor lesions across the body varying within and between patients two days after tracer injection (n = 38, median patient maximum standard uptake value (SUV_max) 5.2, IQI 4.0-7.4). Higher SUV_max was associated with mismatch repair deficiency and longer overall survival. Uptake was higher in lesions with stromal/inflamed than desert immunophenotype. Tissue radioactivity was localized to areas with immunohistochemically confirmed CD8 expression. Re-imaging patients on treatment showed no change in average (geometric mean) tumor tracer uptake compared to baseline, but individual lesions showed diverse changes independent of tumor response. The imaging data suggest enormous heterogeneity in CD8⁺ T cell distribution and pharmacodynamics within and between patients. In conclusion, ⁸⁹ZED88082A can characterize the complex dynamics of CD8⁺ T cells in the context of ICIs, and may inform immunotherapeutic treatments.

Heterogeneity and evolution of tumour immune microenvironment in metastatic gastroesophageal adenocarcinoma

BACKGROUND

Tumour immune microenvironment heterogeneity is prevalent in numerous cancers and can negatively impact immunotherapy response. Immune heterogeneity and evolution in gastroesophageal adenocarcinoma (GEA) have not been studied in the past.

METHODS

Together with a multi-region sampling of normal, primary and metastatic tissues, we performed whole exome sequencing, TCR sequencing as well as immune cell infiltration estimation through deconvolution of gene expression signals.

RESULTS

We discovered high TCR repertoire and immune cell infiltration heterogeneity among metastatic sites, while they were homogeneous among primary and normal samples. Metastatic sites shared high levels of abundant TCR clonotypes with blood, indicating immune surveillance via blood. Metastatic sites also had low levels of tumour-eliminating immune cells and were undergoing heavy immunomodulation compared to normal and primary tumour tissues. There was co-evolution of neo-antigen and TCR repertoire, but only in patients with late diverging mutational evolution. Co-evolution of TCR repertoire and immune cell infiltration was seen in all except one patient.

CONCLUSIONS

Our findings revealed immune heterogeneity and co-evolution in GEA, which may inform immunotherapy decision-making.

LYVE1+ macrophages of murine peritoneal mesothelium promote omentum-independent ovarian tumor growth

Two resident macrophage subsets reside in peritoneal fluid. Macrophages also reside within mesothelial membranes lining the peritoneal cavity, but they remain poorly characterized. Here, we identified two macrophage populations (LYVE1hi MHC IIlo-hi CX3CR1gfplo/- and LYVE1lo/- MHC IIhi CX3CR1gfphi subsets) in the mesenteric and parietal mesothelial linings of the peritoneum. These macrophages resembled LYVE1+ macrophages within surface membranes of numerous organs. Fate-mapping approaches and analysis of newborn mice showed that LYVE1hi macrophages predominantly originated from embryonic-derived progenitors and were controlled by CSF1 made by Wt1+ stromal cells. Their gene expression profile closely overlapped with ovarian tumor-associated macrophages previously described in the omentum. Indeed, syngeneic epithelial ovarian tumor growth was strongly reduced following in vivo ablation of LYVE1hi macrophages, including in mice that received omentectomy to dissociate the role from omental macrophages. These data reveal that the peritoneal compartment contains at least four resident macrophage populations and that LYVE1hi mesothelial macrophages drive tumor growth independently of the omentum.

Evaluation of Response to Immune Checkpoint Inhibitors Using a Radiomics, Lesion-Level Approach

Conventional methods to determine the response to immune checkpoint inhibitors (ICIs) are limited by the unique responses to an ICI. We performed a radiomics approach for all measurable lesions to identify radiomic variables that could distinguish hyperprogressive disease (HPD) on baseline CT scans and classify a dissociated response (DR). One hundred and ninety-six patients with advanced lung cancer, treated with ICI monotherapy, who underwent at least three CT scans, were retrospectively enrolled. For all 621 measurable lesions, HPDv was determined from baseline CT scans using the tumor growth kinetics (TGK) ratio, and radiomics features were extracted. Multivariable logistic regression analysis of radiomics features was performed to discriminate DR. Radiomics features that significantly discriminated HPDv on baseline CT differed according to organ. Of the 196 patients, 54 (27.6%) had a DR and 142 (72.4%) did not have a DR. Overall survival in the group with a DR was significantly inferior to that in the group without a DR (log rank test, p = 0.04). Our study shows that lesion-level analysis using radiomics features has great potential for discriminating HPDv and understanding heterogeneous tumor progression, including a DR, after ICI treatment.

Capturing cancer evolution using genetically engineered mouse models (GEMMs)

Initiating from a single cell, cancer undergoes clonal evolution, leading to a high degree of intratumor heterogeneity (ITH). The arising genetic heterogeneity between cancer cells is influenced by exogenous and endogenous forces that shape the composition of clones within tumors. Preclinical mouse models have provided a valuable tool for understanding cancer, helping to build a fundamental understanding of tumor initiation, progression, and metastasis. Until recently, genetically engineered mouse models (GEMMS) of cancer had lacked the genetic diversity found in human tumors, in which evolution may be driven by long-term carcinogen exposure and DNA damage. However, advances in sequencing technology and in our understanding of the drivers of genetic instability have given us the knowledge to generate new mouse models, offering an approach to functionally explore mechanisms of tumor evolution.

Can integrative biomarker approaches improve prediction of platinum and PARP inhibitor response in ovarian cancer?

Epithelial ovarian carcinoma (EOC) encompasses distinct histological, molecular and genomic entities that determine intrinsic sensitivity to platinum-based chemotherapy. Current management of each subtype is determined by factors including tumour grade and stage, but only a small number of biomarkers can predict treatment response. The recent incorporation of PARP inhibitors into routine clinical practice has underscored the need to personalise ovarian cancer treatment based on tumour biology. In this article, we review the strengths and limitations of predictive biomarkers in current clinical practice and highlight integrative strategies that may inform the development of future personalised medicine programs and composite biomarkers.