Improved computer-assisted analysis of the global lymphatic network in human cervical tissues

Single and combined impacts of irradiation and surgery on lymphatic vasculature and fibrosis associated to secondary lymphedema

Lymphedema (LD) refers to a condition of lymphatic dysfunction associated with excessive fluid accumulation, fibroadipose tissue deposition and swelling. In industrialized countries, LD development mainly results from a local disruption of the lymphatic network by an infection or cancer-related surgery (secondary LD). In the absence of efficient therapy, animal models are needed to decipher the cellular and molecular mechanisms underlying LD and test putative drugs. In this study, we optimized and characterized a murine model of LD that combines an irradiation of the mice hind limb and a radical surgery (lymph node resection associated to lymphatic vessel ligation). We investigated the respective roles of irradiation and surgery in LD formation by comparing their impacts, alone or in combination (with different intervention sequences), on eight different features of the pathology: swelling (paw thickness), indocyanine green (ICG) clearance, lymphatic vasculature remodeling, epidermal and dermal thickening, adipocyte accumulation, inflammatory cell infiltration and collagen deposition. This study supports the importance of radiation prior to surgery to experimentally induce a rapid, severe and sustained tissue remodeling harboring the different hallmarks of LD. We provide the first experimental evidence for an excessive deposition of periostin (POSTN) and tenascin-C (TNC) in LD. Through a computerized method of digital image quantification, we established the spatial map of lymphatic expansion, as well as collagen, POSTN and TNC deposition in papillary and reticular dermis of lymphedematous skins. This mouse model is available to study the patho-physiology of LD and test potential therapeutic targets.

Periostin in lymph node pre-metastatic niches governs lymphatic endothelial cell functions and metastatic colonization

Although lymph node (LN) metastasis is an important prognostic parameter in cervical cancer, the tissue remodeling at a pre-metastatic state is poorly documented in LNs. We here identified periostin (POSTN) as a component of non-metastatic LNs by applying proteomic analyses and computerized image quantifications on LNs of patients with cervical cancer. We provide evidence for remarkable modifications of POSTN and lymphatic vessel distributions and densities in non-metastatic sentinel and metastatic human LNs, when compared to distant non-metastatic LNs. POSTN deposition at a pre-metastatic stage was demonstrated in a pre-clinical murine model (the ear sponge assay). Its expression by fibroblastic LN cells was assessed by in situ hybridization and in vitro cultures. In vitro, POSTN promoted lymphatic endothelial cell functions and tumor cell proliferation. Accordingly, the in vivo injection of recombinant POSTN together with VEGF-C boosted the lymphangiogenic response, while the metastatic potential of tumor cells was drastically reduced using a POSTN blocking antibody. This translational study also supports the existence of an unprecedented dialog “in cascade”, between the primary tumor and the first pelvic nodal relay in early cervical cancer, and subsequently from pelvic LN to para-aortic LNs in locally advanced cervical cancers. Collectively, this work highlights the association of POSTN deposition with lymphangiogenesis in LNs, and provides evidence for a key contribution of POSTN in promoting VEGF-C driven lymphangiogenesis and the seeding of metastatic cells.

Cancer Stem Cells and Their Possible Implications in Cervical Cancer: A Short Review

Cervical cancer (CC) is the fourth most common type of gynecological malignancy affecting females worldwide. Most CC cases are linked to infection with high-risk human papillomaviruses (HPV). There has been a significant decrease in the incidence and death rate of CC due to effective cervical Pap smear screening and administration of vaccines. However, this is not equally available throughout different societies. The prognosis of patients with advanced or recurrent CC is particularly poor, with a one-year relative survival rate of a maximum of 20%. Increasing evidence suggests that cancer stem cells (CSCs) may play an important role in CC tumorigenesis, metastasis, relapse, and chemo/radio-resistance, thus representing potential targets for a better therapeutic outcome. CSCs are a small subpopulation of tumor cells with self-renewing ability, which can differentiate into heterogeneous tumor cell types, thus creating a progeny of cells constituting the bulk of tumors. Since cervical CSCs (CCSC) are difficult to identify, this has led to the search for different markers (e.g., ABCG2, ITGA6 (CD49f), PROM1 (CD133), KRT17 (CK17), MSI1, POU5F1 (OCT4), and SOX2). Promising therapeutic strategies targeting CSC-signaling pathways and the CSC niche are currently under development. Here, we provide an overview of CC and CCSCs, describing the phenotypes of CCSCs and the potential of targeting CCSCs in the management of CC.

Integrated Cells and Collagen Fibers Spatial Image Analysis

Modern technologies designed for tissue structure visualization like brightfield microscopy, fluorescent microscopy, mass cytometry imaging (MCI) and mass spectrometry imaging (MSI) provide large amounts of quantitative and spatial information about cells and tissue structures like vessels, bronchioles etc. Many published reports have demonstrated that the structural features of cells and extracellular matrix (ECM) and their interactions strongly predict disease development and progression. Computational image analysis methods in combination with spatial analysis and machine learning can reveal novel structural patterns in normal and diseased tissue. Here, we have developed a Python package designed for integrated analysis of cells and ECM in a spatially dependent manner. The package performs segmentation, labeling and feature analysis of ECM fibers, combines this information with pre-generated single-cell based datasets and realizes cell-cell and cell-fiber spatial analysis. To demonstrate performance and compatibility of our computational tool, we integrated it with a pipeline designed for cell segmentation, classification, and feature analysis in the KNIME analytical platform. For validation, we used a set of mouse mammary gland tumors and human lung adenocarcinoma tissue samples stained for multiple cellular markers and collagen as the main ECM protein. The developed package provides sufficient performance and precision to be used as a novel method to investigate cell-ECM relationships in the tissue, as well as detect structural patterns correlated with specific disease outcomes.

Tumor-associated neutrophils (TANs) in human carcinoma-draining lymph nodes: a novel TAN compartment

Objectives

The role of tumor‐associated neutrophils (TANs) in the nodal spread of cancer cells remains unexplored. The present study evaluates the occurrence and clinical significance of human nodal TANs.

Methods

The relevance, derivation, phenotype and interactions of nodal TANs were explored via a large immunohistochemical analysis of carcinoma‐draining lymph nodes, and their clinical significance was evaluated on a retrospective cohort of oral squamous cell carcinomas (OSCC). The tumor‐promoting function of nodal TAN was probed in the OSCC TCGA dataset combining TAN and epithelial‐to‐mesenchymal transition (EMT) signatures.

Results

The pan‐carcinoma screening identified a consistent infiltration (59%) of CD66b⁺  TANs in tumor‐draining lymph nodes (TDLNs). Microscopic findings, including the occurrence of intra‐lymphatic conjugates of TANs and cancer cells, indicate that TANs migrate through lymphatic vessels. In vitro experiments revealed that OSCC cell lines sustain neutrophil viability and activation via release of GM‐CSF. Moreover, by retrospective analysis, a high CD66b⁺ TAN density in M‐TDLNs of OSCC (n = 182 patients) predicted a worse prognosis. The analysis of the OSCC‐TCGA dataset unveiled that the expression of a set of neutrophil‐specific genes in the primary tumor (PT) is highly associated with an EMT signature, which predicts nodal spread. Accordingly, in the PT of OSCC cases, CD66b⁺TANs co‐localised with PDPN⁺S100A9⁻ EMT‐switched tumor cells in areas of lymphangiogenesis. The pro‐EMT signature is lacking in peripheral blood neutrophils from OSCC patients, suggesting tissue skewing of TANs.

Conclusion

Our findings are consistent with a novel pro‐tumoral TAN compartment that may promote nodal spread via EMT, through the lymphatics.

Spatial interaction of tumor cells and regulatory T cells correlates with survival in non-small cell lung cancer

OBJECTIVES

To determine the prognostic significance of spatial proximity of lung cancer cells and specific immune cells in the tumor microenvironment.

MATERIALS AND METHODS

We probed formalin-fixed, paraffin-embedded (FFPE) tissue microarrays using a novel tyramide signal amplification multiplexing technique labelling CD8, CD4, Foxp3, and CD68+ cells. Each multiplex stained immunohistochemistry slide was digitally processed by Vectra INFORMS software, and an X- and Y-coordinate assigned to each labeled cell type. The abundance and spatial location of each cell type and their proximity to one another was analyzed using a novel application of the G-cross spatial distance distribution method which computes the probability of finding at least one immune cell of any given type within a rμm radius of a tumor cell. Cox proportional hazards multiple regression was used for multivariate analysis of the influence of proximity of lymphocyte types.

RESULTS

Pathologic tumor specimens from 120 NSCLC patients with pathologic tumor stage I-III disease were analyzed. On univariate analysis, age (P = .0007) and number of positive nodes (P = .0014) were associated with overall survival. Greater area under the curve (AUC) of the G-cross function for tumor cell-Treg interactions was significantly associated with worse survival adjusting for age and number of positive nodes (HR 1.52 (1.11-2.07), P = .009). Greater G-cross AUC for T-reg-CD8 was significantly associated with better survival adjusting for age and number of positive lymph nodes (HR 0.96 (0.92-0.99), P = .042).

CONCLUSION

Increased infiltration of regulatory T cells into core tumor regions is an independent predictor of worse overall survival in NSCLC. However, increased infiltration of CD8+ cytotoxic T cells among regulatory T cells seems to mitigate this effect and was significantly associated with better survival. Validation of the G-cross method of measuring spatial proximity between tumor and immune cell types and exploration of its use as a prognostic factor in lung cancer treatment is warranted.

The timing of surgery after neoadjuvant radiotherapy influences tumor dissemination in a preclinical model

Neoadjuvant radiotherapy (neoRT) used in cancer treatments aims at improving local tumor control and patient overall survival. The neoRT schedule and the timing of the surgical treatment (ST) are empirically based and influenced by the clinician's experience. The current study examines how the sequencing of neoRT and ST affects metastatic dissemination. In a breast carcinoma model, tumors were exposed to different neoRT schedules (2x5Gy or 5x2Gy) followed by surgery at day 4 or 11 post-RT. The impact on the tumor microenvironment and lung metastases was evaluated through immunohistochemical and flow cytometry analyses.

After 2x5Gy, early ST (at day 4 post-RT) led to increased size and number of lung metastases as compared to ST performed at day 11. Inversely, after 5x2Gy neoRT, early ST protected the mice against lung metastases. This intriguing relationship between tumor aggressiveness and ST timing could not be explained by differences in classical parameters studied such as hypoxia, vessel density and matrix remodeling. The study of tumor-related inflammation and immunity reveals an increased circulating NK cell percentage following neoRT as compared to non irradiated mice. Then, radiation treatment and surgery were applied to tumor-bearing NOD/SCID mice. In the absence of NK cells, neoRT appears to increase lung metastatic dissemination as compared to non irradiated tumor-bearing mice.

Altogether our data demonstrate that the neoRT schedule and the ST timing affect metastasis formation in a pre-clinical model and points out the potential role of NK cells. These findings highlight the importance to cautiously tailor the optimal window for ST following RT.

A specific immune and lymphatic profile characterizes the pre-metastatic state of the sentinel lymph node in patients with early cervical cancer

The lymph node (LN) pre-metastatic niche is faintly characterized in lymphophilic human neoplasia, although LN metastasis is considered as the strongest prognostic marker of patient survival. Due to its specific dissemination through a complex bilateral pelvic lymphatic system, early cervical cancer is a relevant candidate for investigating the early nodal metastatic process. In the present study, we analyzed in-depth both the lymphatic vasculature and the immune climate of pre-metastatic sentinel LN (SLN), in 48 cases of FIGO stage IB1 cervical neoplasms. An original digital image analysis methodology was used to objectively determine whole slide densities and spatial distributions of immunostained structures. We observed a marked increase in lymphatic vessel density (LVD) and a specific capsular and subcapsular distribution in pre-metastatic SLN when compared with non-sentinel counterparts. Such features persisted in the presence of nodal metastatic colonization. The inflammatory profile attested by CD8⁺, Foxp3, CD20 and PD-1expression was also significantly increased in pre-metastatic SLN. Remarkably, the densities of CD20⁺ B cells and PD-1 expressing germinal centers were positively correlated with LVD. All together, these data strongly support the existence of a pre-metastatic dialog between the primary tumor and the first nodal relay. Both lymphatic and immune responses contribute to the elaboration of a specific pre-metastatic microenvironment in human SLN. Moreover, this work provides evidence that, in the context of early cervical cancer, a pre-metastatic lymphangiogenesis occurs within the SLN (pre-metastatic niche) and is associated with a specific humoral immune response.

Modeling pre-metastatic lymphvascular niche in the mouse ear sponge assay

Lymphangiogenesis, the formation of new lymphatic vessels, occurs in primary tumors and in draining lymph nodes leading to pre-metastatic niche formation. Reliable in vivo models are becoming instrumental for investigating alterations occurring in lymph nodes before tumor cell arrival. In this study, we demonstrate that B16F10 melanoma cell encapsulation in a biomaterial, and implantation in the mouse ear, prevents their rapid lymphatic spread observed when cells are directly injected in the ear. Vascular remodeling in lymph nodes was detected two weeks after sponge implantation, while their colonization by tumor cells occurred two weeks later. In this model, a huge lymphangiogenic response was induced in primary tumors and in pre-metastatic and metastatic lymph nodes. In control lymph nodes, lymphatic vessels were confined to the cortex. In contrast, an enlargement and expansion of lymphatic vessels towards paracortical and medullar areas occurred in pre-metastatic lymph nodes. We designed an original computerized-assisted quantification method to examine the lymphatic vessel structure and the spatial distribution. This new reliable and accurate model is suitable for in vivo studies of lymphangiogenesis, holds promise for unraveling the mechanisms underlying lymphatic metastases and pre-metastatic niche formation in lymph nodes, and will provide new tools for drug testing.

Spatial Heterogeneity in the Tumor Microenvironment

Recent developments in studies of tumor heterogeneity have provoked new thoughts on cancer management. There is a desperate need to understand influence of the tumor microenvironment on cancer development and evolution. Applying principles and quantitative methods from ecology can suggest novel solutions to fulfil this need. We discuss spatial heterogeneity as a fundamental biological feature of the microenvironment, which has been largely ignored. Histological samples can provide spatial context of diverse cell types coexisting within the microenvironment. Advanced computer-vision techniques have been developed for spatial mapping of cells in histological samples. This has enabled the applications of experimental and analytical tools from ecology to cancer research, generating system-level knowledge of microenvironmental spatial heterogeneity. We focus on studies of immune infiltrate and tumor resource distribution, and highlight statistical approaches for addressing the emerging challenges based on these new approaches.

Cervical cancer stem cells

The concept of cancer stem cells (CSC) has been established over the past decade or so, and their role in carcinogenic processes has been confirmed. In this review, we focus on cervical CSCs, including (1) their purported origin, (2) markers used for cervical CSC identification, (3) alterations to signalling pathways in cervical cancer and (4) the cancer stem cell niche. Although cervical CSCs have not yet been definitively identified and characterized, future studies pursuing them as therapeutic targets may provide novel insights for treatment of cervical cancer.

Assessing Tumor Angiogenesis in Histological Samples

Tumor neovascularization acquires their vessels through a number of processes including angiogenesis, vasculogenesis, vascular remodeling, intussusception, and possibly vascular mimicry in certain tumors. The end result of the tumor vasculature has been quantified by counting the number of immunohistochemically identified microvessels in areas of maximal vascularity, so-called hot spot. Other techniques have been developed such as Chalkley counting and the use of image analysis systems that are robust and reproducible as well as being more objective. Many of the molecular pathways that govern tumor neovascularization have been identified and many reagents are now available to study these tissue sections. These include angiogenic growth factors and their receptors and cell adhesion molecules, proteases, and markers of activated, proliferating, cytokine-stimulated, or angiogenic vessels, such as CD105. It is also possible to differentiate quiescent from active vessels. Other reagents that can identify proteins involved in microenvironmental influences such as hypoxia have also been generated. Although the histological assessment of tumor vascularity is used mostly in the research context, it may also have clinical applications if appropriate methodology and trained observers perform the studies.

Computational pathology: Exploring the spatial dimension of tumor ecology

Tumors are evolving ecosystems where cancer subclones and the microenvironment interact. This is analogous to interaction dynamics between species in their natural habitats, which is a prime area of study in ecology. Spatial statistics are frequently used in ecological studies to infer complex relations including predator-prey, resource dependency and co-evolution. Recently, the emerging field of computational pathology has enabled high-throughput spatial analysis by using image processing to identify different cell types and their locations within histological tumor samples. We discuss how these data may be analyzed with spatial statistics used in ecology to reveal patterns and advance our understanding of ecological interactions occurring among cancer cells and their microenvironment.

TissueCypher(™): A systems biology approach to anatomic pathology

Background:

Current histologic methods for diagnosis are limited by intra- and inter-observer variability. Immunohistochemistry (IHC) methods are frequently used to assess biomarkers to aid diagnoses, however, IHC staining is variable and nonlinear and the manual interpretation is subjective. Furthermore, the biomarkers assessed clinically are typically biomarkers of epithelial cell processes. Tumors and premalignant tissues are not composed only of epithelial cells but are interacting systems of multiple cell types, including various stromal cell types that are involved in cancer development. The complex network of the tissue system highlights the need for a systems biology approach to anatomic pathology, in which quantification of system processes is combined with informatics tools to produce actionable scores to aid clinical decision-making.

Aims:

Here, we describe a quantitative, multiplexed biomarker imaging approach termed TissueCypher™ that applies systems biology to anatomic pathology. Applications of TissueCypher™ in understanding the tissue system of Barrett's esophagus (BE) and the potential use as an adjunctive tool in the diagnosis of BE are described.

Patients and Methods:

The TissueCypher™ Image Analysis Platform was used to assess 14 epithelial and stromal biomarkers with known diagnostic significance in BE in a set of BE biopsies with nondysplastic BE with reactive atypia (RA, n = 22) and Barrett's with high-grade dysplasia (HGD, n = 17). Biomarker and morphology features were extracted and evaluated in the confirmed BE HGD cases versus the nondysplastic BE cases with RA.

Results:

Multiple image analysis features derived from epithelial and stromal biomarkers, including immune biomarkers and morphology, showed significant differences between HGD and RA.

Conclusions:

The assessment of epithelial cell abnormalities combined with an assessment of cellular changes in the lamina propria may serve as an adjunct to conventional pathology in the assessment of BE.

Beyond immune density: critical role of spatial heterogeneity in estrogen receptor-negative breast cancer

The abundance of tumor-infiltrating lymphocytes has been associated with a favorable prognosis in estrogen receptor-negative breast cancer. However, a high degree of spatial heterogeneity in lymphocytic infiltration is often observed and its clinical implication remains unclear. Here we combine automated histological image processing with methods of spatial statistics used in ecological data analysis to quantify spatial heterogeneity in the distribution patterns of tumor-infiltrating lymphocytes. Hematoxylin and eosin-stained sections from two cohorts of estrogen receptor-negative breast cancer patients (discovery: n=120; validation: n=125) were processed with our automated cell classification algorithm to identify the location of lymphocytes and cancer cells. Subsequently, hotspot analysis (Getis-Ord Gi*) was applied to identify statistically significant hotspots of cancer and immune cells, defined as tumor regions with a significantly high number of cancer cells or immune cells, respectively. We found that the amount of co-localized cancer and immune hotspots weighted by tumor area, rather than number of cancer or immune hotspots, correlates with a better prognosis in estrogen receptor-negative breast cancer in univariate and multivariate analysis. Moreover, co-localization of cancer and immune hotspots further stratified patients with immune cell-rich tumors. Our study demonstrates the importance of quantifying not only the abundance of lymphocytes but also their spatial variation in the tumor specimen for which methods from other disciplines such as spatial statistics can be successfully applied.

Mapping spatial heterogeneity in the tumor microenvironment: a new era for digital pathology

The emergent field of digital pathology employing automated image analysis techniques is to revolutionize traditional pathology at the center of clinical diagnostics. Histological images provide important tumor features unavailable in molecular profiling or omics data- the spatial context of tumor and stromal cells at single-cell resolution. Methods to map the spatial and morphological patterns of cancer and normal cells can contribute to a more comprehensive understanding of the highly heterogeneous tumor microenvironment. This review focuses on methods that help expand our knowledge of intra-tumoral spatial heterogeneity of the tumor microenvironment and their potential synergies with molecular profiling technologies.