Showing papers by "Wolf H. Fridman published in 2019"

Tertiary lymphoid structures in the era of cancer immunotherapy

Abstract: Tertiary lymphoid structures (TLSs) are ectopic lymphoid organs that develop in non-lymphoid tissues at sites of chronic inflammation including tumours. Key common characteristics between secondary lymphoid organogenesis and TLS neogenesis have been identified. TLSs exist under different maturation states in tumours, culminating in germinal centre formation. The mechanisms that underlie the role of TLSs in the adaptive antitumour immune response are being deciphered. The description of the correlation between TLS presence and clinical benefit in patients with cancer, suggesting that TLSs could be a prognostic and predictive factor, has drawn strong interest into investigating the role of TLSs in tumours. A current major challenge is to exploit TLSs to promote lymphocyte infiltration, activation by tumour antigens and differentiation to increase the antitumour immune response. Several approaches are being developed using chemokines, cytokines, antibodies, antigen-presenting cells or synthetic scaffolds to induce TLS formation. Strategies aiming to induce TLS neogenesis in immune-low tumours and in immune-high tumours, in this case, in combination with therapeutic agents dampening the inflammatory environment and/or with immune checkpoint inhibitors, represent promising avenues for cancer treatment.

Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology

Abstract: Motivation The composition and density of immune cells in the tumor microenvironment (TME) profoundly influence tumor progression and success of anti-cancer therapies. Flow cytometry, immunohistochemistry staining or single-cell sequencing are often unavailable such that we rely on computational methods to estimate the immune-cell composition from bulk RNA-sequencing (RNA-seq) data. Various methods have been proposed recently, yet their capabilities and limitations have not been evaluated systematically. A general guideline leading the research community through cell type deconvolution is missing. Results We developed a systematic approach for benchmarking such computational methods and assessed the accuracy of tools at estimating nine different immune- and stromal cells from bulk RNA-seq samples. We used a single-cell RNA-seq dataset of ∼11 000 cells from the TME to simulate bulk samples of known cell type proportions, and validated the results using independent, publicly available gold-standard estimates. This allowed us to analyze and condense the results of more than a hundred thousand predictions to provide an exhaustive evaluation across seven computational methods over nine cell types and ∼1800 samples from five simulated and real-world datasets. We demonstrate that computational deconvolution performs at high accuracy for well-defined cell-type signatures and propose how fuzzy cell-type signatures can be improved. We suggest that future efforts should be dedicated to refining cell population definitions and finding reliable signatures. Availability and implementation A snakemake pipeline to reproduce the benchmark is available at https://github.com/grst/immune_deconvolution_benchmark. An R package allows the community to perform integrated deconvolution using different methods (https://grst.github.io/immunedeconv). Supplementary information Supplementary data are available at Bioinformatics online.

The clinical role of the TME in solid cancer.

Abstract: The highly complex and heterogenous ecosystem of a tumour not only contains malignant cells, but also interacting cells from the host such as endothelial cells, stromal fibroblasts, and a variety of immune cells that control tumour growth and invasion. It is well established that anti-tumour immunity is a critical hurdle that must be overcome for tumours to initiate, grow and spread and that anti-tumour immunity can be modulated using current immunotherapies to achieve meaningful anti-tumour clinical responses. Pioneering studies in melanoma, ovarian and colorectal cancer have demonstrated that certain features of the tumour immune microenvironment (TME)-in particular, the degree of tumour infiltration by cytotoxic T cells-can predict a patient's clinical outcome. More recently, studies in renal cell cancer have highlighted the importance of assessing the phenotype of the infiltrating T cells to predict early relapse. Furthermore, intricate interactions with non-immune cellular players such as endothelial cells and fibroblasts modulate the clinical impact of immune cells in the TME. Here, we review the critical components of the TME in solid tumours and how they shape the immune cell contexture, and we summarise numerous studies evaluating its clinical significance from a prognostic and theranostic perspective.

Context-dependent roles of complement in cancer

Abstract: The tumour microenvironment (TME) highly influences the growth and spread of tumours, thus impacting the patient's clinical outcome. In this context, the complement system plays a major and complex role. It may either act to kill antibody-coated tumour cells, support local chronic inflammation or hamper antitumour T cell responses favouring tumour progression. Recent studies demonstrate that these opposing effects are dependent upon the sites of complement activation, the composition of the TME and the tumour cell sensitivity to complement attack. In this Review, we present the evidence that has so far accrued showing a role for complement activation and its effects on cancer control and clinical outcome under different TME contexts. We also include a new analysis of the publicly available transcriptomic data to provide an overview of the prognostic value of complement gene expression in 30 cancer types. We argue that the interplay of complement components within each cancer type is unique, governed by the properties of the tumour cells and the TME. This concept is of critical importance for the design of efficient therapeutic strategies aimed at targeting complement components and their signalling.

Tumor Cells Hijack Macrophage-Produced Complement C1q to Promote Tumor Growth

Abstract: Clear-cell renal cell carcinoma (ccRCC) possesses an unmet medical need, particularly at the metastatic stage, when surgery is ineffective. Complement is a key factor in tissue inflammation, favoring cancer progression through the production of complement component 5a (C5a). However, the activation pathways that generate C5a in tumors remain obscure. By data mining, we identified ccRCC as a cancer type expressing concomitantly high expression of the components that are part of the classical complement pathway. To understand how the complement cascade is activated in ccRCC and impacts patients' clinical outcome, primary tumors from three patient cohorts (n = 106, 154, and 43), ccRCC cell lines, and tumor models in complement-deficient mice were used. High densities of cells producing classical complement pathway components C1q and C4 and the presence of C4 activation fragment deposits in primary tumors correlated with poor prognosis. The in situ orchestrated production of C1q by tumor-associated macrophages (TAM) and C1r, C1s, C4, and C3 by tumor cells associated with IgG deposits, led to C1 complex assembly, and complement activation. Accordingly, mice deficient in C1q, C4, or C3 displayed decreased tumor growth. However, the ccRCC tumors infiltrated with high densities of C1q-producing TAMs exhibited an immunosuppressed microenvironment, characterized by high expression of immune checkpoints (i.e., PD-1, Lag-3, PD-L1, and PD-L2). Our data have identified the classical complement pathway as a key inflammatory mechanism activated by the cooperation between tumor cells and TAMs, favoring cancer progression, and highlight potential therapeutic targets to restore an efficient immune reaction to cancer.

Association of IL-36γ with tertiary lymphoid structures and inflammatory immune infiltrates in human colorectal cancer.

Abstract: IL-1 family cytokines play a dual role in the gut, with different family members contributing either protective or pathogenic effects. IL-36γ is an IL-1 family cytokine involved in polarizing type-1 immune responses. However, its function in the gut, including in colorectal cancer pathogenesis, is not well appreciated. In a murine model of colon carcinoma, IL-36γ controls tertiary lymphoid structure formation and promotes a type-1 immune response concurrently with a decrease in expression of immune checkpoint molecules in the tumor microenvironment. Here, we demonstrate that IL-36γ plays a similar role in driving a pro-inflammatory phenotype in human colorectal cancer. We analyzed a cohort of 33 primary colorectal carcinoma tumors using imaging, flow cytometry, and transcriptomics to determine the pattern and role of IL-36γ expression in this disease. In the colorectal tumor microenvironment, we observed IL-36γ to be predominantly expressed by M1 macrophages and cells of the vasculature, including smooth muscle cells and high endothelial venules. This pattern of IL-36γ expression is associated with a CD4+ central memory T cell infiltrate and an increased density of B cells in tertiary lymphoid structures, as well as with markers of fibrosis. Conversely, expression of the antagonist to IL-36 signaling, IL-1F5, was associated with intratumoral expression of checkpoint molecules, including PD-1, PD-L1, and CTLA4, which can suppress the immune response. These data support a role for IL-36γ in the physiologic immune response to colorectal cancer by sustaining inflammation within the tumor microenvironment.

Guadecitabine Plus Ipilimumab in Unresectable Melanoma: The NIBIT-M4 Clinical Trial.

Abstract: Purpose: The immuno-modulatory activity of DNA hypomethylating agents (DHA) suggests they may improve the effectiveness of cancer immunotherapies. The phase 1b NIBIT-M4 trial tested this hypothesis using the next-generation DHA guadecitabine combined with ipilimumab. Experimental Design: Unresectable Stage III/IV melanoma patients received escalating doses of guadecitabine 30, 45 or 60 mg/m2/day subcutaneously on Days 1-5 every 3 weeks, and ipilimumab 3 mg/kg intravenously on Day 1 every 3 weeks, starting 1 week after guadecitabine, for 4 cycles. Primary endpoints were safety, tolerability and maximum tolerated dose of treatment; secondary were immune-related (ir) disease control rate (DCR) and objective response rate (ORR); exploratory were changes in methylome, transcriptome, and immune contextures in sequential tumor biopsies, and pharmacokinetics. Results: Nineteen patients were treated; 84% had grade 3/4 adverse events, neither dose limiting toxicities per protocol nor overlapping toxicities were observed. Ir-DCR and ir-ORR were 42% and 26%, respectively. Median CpG site methylation of tumor samples (n=8) at Week 4 (74.5%) and Week 12 (75.5%) was significantly (p 2 or

Revisiting immune escape in colorectal cancer in the era of immunotherapy.

Abstract: In colorectal cancer (CRC), T-cell checkpoint blockade is only effective in patients diagnosed with mismatch repair-deficient (MMR-d) cancers. However, defects in Human Leukocyte Antigen (HLA) class I expression were reported to occur in most MMR-d CRCs, which would preclude antigen presentation in these tumours, considered essential for the clinical activity of this immunotherapeutic modality. We revisited this paradox by characterising HLA class I expression in two independent cohorts of CRC. We determined that loss of HLA class I expression occurred in the majority (73–78%) of MMR-d cases. This phenotype was rare in CRC liver metastases, irrespective of MMR status, whereas weak, inducible expression of HLA class I molecules was frequent in liver lesions. We propose that HLA class I is an important determinant of metastatic homing in CRCs. This observation is paramount to understand CRC carcinogenesis and for the application of immunotherapies in the metastatic setting.

Integrating histopathology, immune biomarkers, and molecular subgroups in solid cancer: the next step in precision oncology.

Abstract: For many years, the gold standard cancer grading and staging had focused on the characteristics of the cancer cells and often disregarded the non-tumoral cell compartments. The expansion of research on the tumor immune microenvironment, the successes and dissemination of immunotherapies to treat cancer, and the open access to large -omic databases have allowed the development of novel powerful immune-based prognostic and theranostic biomarkers. Although they often correlate with histopathologic characteristics and TNM staging, in many instances, they are independently associated with, and potentially superior predictors of, the patient's prognosis and response to immunotherapies. As pathologists in the era of precision medicine, we are uniquely positioned to participate in the integration of these histologic and molecular features of the tumor microenvironment to provide the best prognostic information to clinicians and patients. In this review, we summarize some of the most important immune-related prognostic biomarkers in solid cancer, how they integrate with traditional histopathologic (i.e., staging and grading) and novel molecular stratification systems, and their potential role as predictors to response to agents blocking the PD-1/PD-L1 axis.

Comprehensive evaluation of computational cell-type quantification methods for immuno-oncology

Abstract: Motivation The composition and density of immune cells in the tumor microenvironment profoundly influence tumor progression and success of anti-cancer therapies. Flow cytometry, immunohistochemistry staining, or single-cell sequencing is often unavailable such that we rely on computational methods to estimate the immune-cell composition from bulk RNA-sequencing (RNA-seq) data. Various methods have been proposed recently, yet their capabilities and limitations have not been evaluated systematically. A general guideline leading the research community through cell type deconvolution is missing. Results We developed a systematic approach for benchmarking such computational methods and assessed the accuracy of tools at estimating nine different immune- and stromal cells from bulk RNA-seq samples. We used a single-cell RNA-seq dataset of ∼11,000 cells from the tumor microenvironment to simulate bulk samples of known cell type proportions, and validated the results using independent, publicly available gold-standard estimates. This allowed us to analyze and condense the results of more than a hundred thousand predictions to provide an exhaustive evaluation across seven computational methods over nine cell types and ∼1,800 samples from five simulated and real-world datasets. We demonstrate that computational deconvolution performs at high accuracy for well-defined cell-type signatures and propose how fuzzy cell-type signatures can be improved. We suggest that future efforts should be dedicated to refining cell population definitions and finding reliable signatures. Availability A snakemake pipeline to reproduce the benchmark is available at https://github.com/grst/immune_deconvolution_benchmark. An R package allows the community to perform integrated deconvolution using different methods (https://grst.github.io/immunedeconv). Contact g.sturm@tum.de Supplementary information Supplementary data are available at Bioinformatics online.

Addressing current challenges and future directions in immuno-oncology: expert perspectives from the 2017 NIBIT Foundation Think Tank, Siena, Italy.

Abstract: A collaborative think tank involving panellists from immuno-oncology networks, clinical/translational investigators and the pharmaceutical industry was held in Siena, Italy, in October 2017 to discuss the evolving immune-oncology landscape, identify selected key challenges, and provide a perspective on the next steps required in the translation of current research and knowledge to clinical reality. While there is a trend of combining new agents (e.g., co-stimulator agonists) with a PD-1/PD-L1 treatment backbone, use of alternative combination therapy approaches should also be considered. While the rapid evolution in systems biology provides a deeper understanding of tumor and tumor microenvironment heterogeneity, there remains the need to identify and define genuinely predictive biomarkers to guide treatment and patient selection. Cross-specialty and cross-sector collaboration, along with a broader collective data-sharing approach are key to optimizing immuno-oncology therapy in clinical practice. Continued support of younger research-clinicians is essential for future success in clinical, translational and basic science investigations.

MS.liverK: An R package for transcriptome-based computation of molecular subtypes and functional signatures in liver cancer

Abstract: Summary Liver cancer is a highly heterogeneous disease in terms of etiology, tissue and cellular morphology, tumor molecular characteristics, microenvironment composition and prognosis. Several studies, based on tumor gene-expression profiling (GEP) data, have dissected the molecular heterogeneity of liver cancer. They resulted in various tools, either delineating homogeneous tumor subtypes or calculating molecular scores of prognostic or biological functions. Here, we present MS.liverK, an easy-to-use R package providing a comprehensive implementation of these tools, for research use. Availability and implementation The MS.liverK R package is available from GitHub (https://github.com/cit-bioinfo/MS.liverK).