A COL11A1-correlated pan-cancer gene signature of activated fibroblasts for the prioritization of therapeutic targets

Overexpression of COL11A1 confers tamoxifen resistance in breast cancer

Breast cancer is the most commonly diagnosed malignancy and benefits from endocrine agents such as tamoxifen. However, the development of drug resistance in cancerous cells often leads to recurrence, thus limiting the therapeutic benefit. Identification of potential biomarkers that can predict response to tamoxifen and recognize patients who will clinically benefit from this therapy is urgently needed. In this study, we report that high collagen type XI alpha 1 (COL11A1) expression was associated with poor therapeutic response and prognosis in breast cancer patients treated with tamoxifen. To confirm the role of COL11A1 in the development of tamoxifen resistance, we established MCF-7/COL11A1 and T47D/COL11A1 cell lines, which stably expressed COL11A1. Compared with parental MCF-7 and T47D, MCF-7/COL11A1 and T47D/COL11A1 cells were more resistant to 4-OHT-induced growth inhibition. Moreover, the level of COL11A1 expression was upregulated in tamoxifen-resistant MCF-7/TamR and T47D/TamR cell lines, and depletion of COL11A1 markedly sensitized the cells to 4-OHT in vitro and in vivo. Interestingly, the level of estrogen receptor α (ERα) expression was elevated, probably due to the increased COL11A1 in TamR cells. In addition, knockdown of COL11A1 decreased the expression of ERα and its downstream target genes. Overall, our findings suggest that overexpressed COL11A1 contributes to tamoxifen resistance, and targeting COL11A1 holds great promise for reversing endocrine resistance.

Integrins as the pivotal regulators of cisplatin response in tumor cells

Cisplatin (CDDP) is a widely used first-line chemotherapeutic drug in various cancers. However, CDDP resistance is frequently observed in cancer patients. Therefore, it is required to evaluate the molecular mechanisms associated with CDDP resistance to improve prognosis among cancer patients. Integrins are critical factors involved in tumor metastasis that regulate cell-matrix and cell-cell interactions. They modulate several cellular mechanisms including proliferation, invasion, angiogenesis, polarity, and chemo resistance. Modification of integrin expression levels can be associated with both tumor progression and inhibition. Integrins are also involved in drug resistance of various solid tumors through modulation of the tumor cell interactions with interstitial matrix and extracellular matrix (ECM). Therefore, in the present review we discussed the role of integrin protein family in regulation of CDDP response in tumor cells. It has been reported that integrins mainly promoted the CDDP resistance through interaction with PI3K/AKT, MAPK, and WNT signaling pathways. They also regulated the CDDP mediated apoptosis in tumor cells. This review paves the way to suggest the integrins as the reliable therapeutic targets to improve CDDP response in tumor cells.

Analysis of cancer-associated fibroblasts related genes identifies COL11A1 associated with lung adenocarcinoma prognosis

BACKGROUND

The treatment of lung adenocarcinoma is difficult due to the limited therapeutic options. Cancer-associated fibroblasts play an important role in the development of cancers. This study aimed to identify a promising molecular target associated with cancer-associated fibroblasts for the treatment of lung adenocarcinoma.

METHODS

The Cancer Genome Atlas lung adenocarcinoma dataset was used to screen hub genes associated with cancer-associated fibroblasts via the EPIC algorithm and Weighted Gene Co-expression Network Analysis. Multiple databases were used together with our data to verify the differential expression and survival of COL11A1. Functional enrichment analysis and the single-cell TISCH database were used to elucidate the mechanisms underlying COL11A1 expression. The correlation between COL11A1 and immune checkpoint genes in human cancers was also evaluated.

RESULTS

Using the EPIC algorithm and Weighted Gene Co-expression Network Analysis, 13 hub genes associated with cancer-associated fibroblasts in lung adenocarcinoma were screened. Using the GEPIA database, Kaplan-Meier Plotter database, GSE72094, GSE75037, GSE32863, and our immunohistochemistry experiment data, we confirmed that COL11A1 overexpresses in lung adenocarcinoma and that high expression of COL11A1 is associated with a poor prognosis. COL11A1 has a genetic alteration frequency of 22% in patients with lung adenocarcinoma. COL11A1 is involved in the extracellular matrix activities of lung adenocarcinoma. Using the TISCH database, we found that COL11A1 is mainly expressed by cancer-associated fibroblasts in the tumor microenvironment rather than by lung adenocarcinoma cells. Finally, we found that COL11A1 is positively correlated with HAVCR2(TIM3), CD274 (PD-L1), CTLA4, and LAG3 in lung adenocarcinoma.

CONCLUSION

COL11A1 may be expressed and secreted by cancer-associated fibroblasts, and a high expression of COL11A1 may result in T cell exhaustion in the tumor microenvironment of lung adenocarcinoma. COL11A1 may serve as an attractive biomarker to provide new insights into cancer therapeutics.

Spatiotemporal architecture of immune cells and cancer-associated fibroblasts in high-grade serous ovarian carcinoma

High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically diagnosed after it has metastasized and often relapses after standard-of-care platinum-based chemotherapy, likely due to advanced tumor stage, heterogeneity, and immune evasion and tumor-promoting signaling from the tumor microenvironment. To understand how spatial heterogeneity contributes to HGSOC progression and early relapse, we profiled an HGSOC tissue microarray of patient-matched longitudinal samples from 42 patients. We found spatial patterns associated with early relapse, including changes in T cell localization, malformed tertiary lymphoid structure (TLS)-like aggregates, and increased podoplanin-positive cancer-associated fibroblasts (CAFs). Using spatial features to compartmentalize the tissue, we found that plasma cells distribute in two different compartments associated with TLS-like aggregates and CAFs, and these distinct microenvironments may account for the conflicting reports about the role of plasma cells in HGSOC prognosis.

Scientific and clinical relevance of non-cellular tumor microenvironment components in ovarian cancer chemotherapy resistance

The tumor microenvironment (TME) components play a crucial role in cancer cells' resistance to chemotherapeutic agents. This phenomenon is exceptionally fundamental in patients with ovarian cancer (OvCa), whose outcome depends mainly on their response to chemotherapy. Until now, most reports have focused on the role of cellular components of the TME, while less attention has been paid to the stroma and other non-cellular elements of the TME, which may play an essential role in the therapy resistance. Inhibiting these components could help define new therapeutic targets and potentially restore chemosensitivity. The aim of the present article is both to summarize the knowledge about non-cellular components of the TME in the development of OvCa chemoresistance and to suggest targeting of non-cellular elements of the TME as a valuable strategy to overcome chemoresistance and to develop new therapeutic strategies in OvCA patients.

Novel CAF-identifiers via transcriptomic and protein level analysis in HNSC patients

Cancer-associated fibroblasts (CAFs), a prominent component of the tumor microenvironment, play an important role in tumor development, invasion, and drug resistance. The expression of distinct "CAF-markers" which separates CAFs from normal fibroblasts and epithelial cells, have traditionally been used to identify them. These commonly used CAF-markers have been reported to differ greatly across different CAF subpopulations, even within a cancer type. Using an unbiased -omic approach from public data and in-house RNAseq data from patient derived novel CAF cells, TIMP-1, SPARC, COL1A2, COL3A1 and COL1A1 were identified as potential CAF-markers by differential gene expression analysis using publicly available single cell sequencing data and in-house RNAseq data to distinguish CAF populations from tumor epithelia and normal oral fibroblasts. Experimental validation using qPCR and immunofluorescence revealed CAF-specific higher expression of TIMP-1 and COL1A2 as compared to other markers in 5 novel CAF cells, derived from patients of diverse gender, habits and different locations of head and neck squamous cell carcinoma (HNSC). Upon immunohistochemical (IHC) analysis of FFPE blocks however, COL1A2 showed better differential staining between tumor epithelia and tumor stroma. Similar data science driven approach utilizing single cell sequencing and RNAseq data from stabilized CAFs can be employed to identify CAF-markers in various cancers.

Targeting Oncogenic Wnt/β-Catenin Signaling in Adrenocortical Carcinoma Disrupts ECM Expression and Impairs Tumor Growth

Adrenocortical carcinoma (ACC) is a rare but highly aggressive cancer with limited treatment options and poor survival for patients with advanced disease. An improved understanding of the transcriptional programs engaged in ACC will help direct rational, targeted therapies. Whereas activating mutations in Wnt/β-catenin signaling are frequently observed, the β-catenin-dependent transcriptional targets that promote tumor progression are poorly understood. To address this question, we analyzed ACC transcriptome data and identified a novel Wnt/β-catenin-associated signature in ACC enriched for the extracellular matrix (ECM) and predictive of poor survival. This suggested an oncogenic role for Wnt/β-catenin in regulating the ACC microenvironment. We further investigated the minor fibrillar collagen, collagen XI alpha 1 (COL11A1), and found that COL11A1 expression originates specifically from cancer cells and is strongly correlated with both Wnt/β-catenin activation and poor patient survival. Inhibition of constitutively active Wnt/β-catenin signaling in the human ACC cell line, NCI-H295R, significantly reduced the expression of COL11A1 and other ECM components and decreased cancer cell viability. To investigate the preclinical potential of Wnt/β-catenin inhibition in the adrenal microenvironment, we developed a minimally invasive orthotopic xenograft model of ACC and demonstrated that treatment with the newly developed Wnt/β-catenin:TBL1 inhibitor Tegavivint significantly reduced tumor growth. Together, our data support that the inhibition of aberrantly active Wnt/β-catenin disrupts transcriptional reprogramming of the microenvironment and reduces ACC growth and survival. Furthermore, this β-catenin-dependent oncogenic program can be therapeutically targeted with a newly developed Wnt/β-catenin inhibitor. These results show promise for the further clinical development of Wnt/β-catenin inhibitors in ACC and unveil a novel Wnt/β-catenin-regulated transcriptome.

What is new in cancer-associated fibroblast biomarkers?

The tumor microenvironment is one of the important drivers of tumor development. Cancer-associated fibroblasts (CAFs) are a major component of the tumor stroma and actively participate in tumor development, invasion, metastasis, drug resistance, and other biological behaviors. CAFs are a highly heterogeneous group of cells, a reflection of the diversity of their origin, biomarkers, and functions. The diversity of CAF origin determines the complexity of CAF biomarkers, and CAF subpopulations expressing different biomarkers may play contrasting roles in tumor progression. In this review, we provide an overview of these emerging CAF biomarkers and the biological functions that they suggest, which may give a better understanding of the relationship between CAFs and tumor cells and be of great significance for breakthroughs in precision targeted therapy for tumors. Video Abstract.

Phase-specific signatures of wound fibroblasts and matrix patterns define cancer-associated fibroblast subtypes

Healing wounds and cancers present remarkable cellular and molecular parallels, but the specific roles of the healing phases are largely unknown. We developed a bioinformatics pipeline to identify genes and pathways that define distinct phases across the time-course of healing. Their comparison to cancer transcriptomes revealed that a resolution phase wound signature is associated with increased severity in skin cancer and enriches for extracellular matrix-related pathways. Comparisons of transcriptomes of early- and late-phase wound fibroblasts vs skin cancer-associated fibroblasts (CAFs) identified an "early wound" CAF subtype, which localizes to the inner tumor stroma and expresses collagen-related genes that are controlled by the RUNX2 transcription factor. A "late wound" CAF subtype localizes to the outer tumor stroma and expresses elastin-related genes. Matrix imaging of primary melanoma tissue microarrays validated these matrix signatures and identified collagen- vs elastin-rich niches within the tumor microenvironment, whose spatial organization predicts survival and recurrence. These results identify wound-regulated genes and matrix patterns with prognostic potential in skin cancer.

Single-cell analysis reveals the COL11A1+ fibroblasts are cancer-specific fibroblasts that promote tumor progression

Background: Cancer-associated fibroblasts (CAFs) promote tumor progression through extracellular matrix (ECM) remodeling and extensive communication with other cells in tumor microenvironment. However, most CAF-targeting strategies failed in clinical trials due to the heterogeneity of CAFs. Hence, we aimed to identify the cluster of tumor-promoting CAFs, elucidate their function and determine their specific membrane markers to ensure precise targeting. Methods: We integrated multiple single-cell RNA sequencing (scRNA-seq) datasets across different tumors and adjacent normal tissues to identify the tumor-promoting CAF cluster. We analyzed the origin of these CAFs by pseudotime analysis, and tried to elucidate the function of these CAFs by gene regulatory network analysis and cell-cell communication analysis. We also performed cell-type deconvolution analysis to examine the association between the proportion of these CAFs and patients' prognosis in TCGA cancer cohorts, and validated that through IHC staining in clinical tumor tissues. In addition, we analyzed the membrane molecules in different fibroblast clusters, trying to identify the membrane molecules that were specifically expressed on these CAFs. Results: We found that COL11A1+ fibroblasts specifically exist in tumor tissues but not in normal tissues and named them cancer-specific fibroblasts (CSFs). We revealed that these CSFs were transformed from normal fibroblasts. CSFs represented a more activated CAF cluster and may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. High CSF proportion was associated with poor prognosis in bladder cancer (BCa) and lung adenocarcinoma (LUAD), and IHC staining of COL11A1 confirmed their specific expression in tumor stroma in clinical BCa samples. We also identified that CSFs specifically express the membrane molecules LRRC15, ITGA11, SPHK1 and FAP, which could distinguish CSFs from other fibroblasts. Conclusion: We identified that CSFs is a tumor specific cluster of fibroblasts, which are in active state, may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. Membrane molecules LRRC15, ITGA11, SPHK1 and FAP could be used as therapeutic targets for CSF-targeting cancer treatment.

Integrin α11β1 in tumor fibrosis: more than just another cancer-associated fibroblast biomarker?

There is currently an increased interest in understanding the role of the tumor microenvironment (TME) in tumor growth and progression. In this context the role of integrins in cancer-associated fibroblasts (CAFs) will need to be carefully re-evaluated. Fibroblast-derived cells are not only in the focus in tumors, but also in tissue fibrosis as well as in inflammatory conditions. The recent transcriptional profiling of what has been called "the pan-fibroblast cell lineage" in mouse and human tissues has identified novel transcriptional biomarker mRNAs encoding the secreted ECM proteins dermatopontin and collagen XV as well as the phosphatidylinositol-anchored membrane protein Pi16. Some of the genes identified in these fibroblasts scRNA-seq datasets will be useful for rigorous comparative characterizations of fibroblast-derived cell subpopulations. At the same time, it will be a challenge in the coming years to validate these transcriptional mRNA datasets at the protein-(expression) and at tissue-(distribution) levels and to find useful protein biomarker reagents that will facilitate fibroblast profiling at the cell level. In the current review we will focus on the role of the collagen-binding integrin α11β1 in CAFs, summarizing our own work as well as published datasets with information on α11 mRNA expression in selected tumors. Our experimental data suggest that α11β1 is more than just another biomarker and that it as a functional collagen receptor in the TME is playing a central role in regulating collagen assembly and matrix remodeling, which in turn impact tumor growth and metastasis.

Dynamic Changes in the Extracellular Matrix in Primary, Metastatic, and Recurrent Ovarian Cancers

Cancer-associated fibroblasts (CAFs) and their extracellular matrix are active participants in cancer progression. While it is known that functionally different subpopulations of CAFs co-exist in ovarian cancer, it is unclear whether certain CAF subsets are enriched during metastatic progression and/or chemotherapy. Using computational image analyses of patient-matched primary high-grade serous ovarian carcinomas, synchronous pre-chemotherapy metastases, and metachronous post-chemotherapy metastases from 42 patients, we documented the dynamic spatiotemporal changes in the extracellular matrix, fibroblasts, epithelial cells, immune cells, and CAF subsets expressing different extracellular matrix components. Among the different CAF subsets, COL11A1+ CAFs were associated with linearized collagen fibers and exhibited the greatest enrichment in pre- and post-chemotherapy metastases compared to matched primary tumors. Although pre- and post-chemotherapy metastases were associated with increased CD8+ T cell infiltration, the infiltrate was not always evenly distributed between the stroma and cancer cells, leading to an increased frequency of the immune-excluded phenotype where the majority of CD8+ T cells are present in the tumor stroma but absent from the tumor parenchyma. Overall, most of the differences in the tumor microenvironment were observed between primary tumors and metastases, while fewer differences were observed between pre- and post-treatment metastases. These data suggest that the tumor microenvironment is largely determined by the primary vs. metastatic location of the tumor while chemotherapy does not have a significant impact on the host microenvironment.

Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning

Cancer is one of the leading causes of death worldwide and can be caused by environmental aspects (for example, exposure to asbestos), by human behavior (such as smoking), or by genetic factors. To understand which genes might be involved in patients’ survival, researchers have invented prognostic genetic signatures: lists of genes that can be used in scientific analyses to predict if a patient will survive or not. In this study, we joined together five different prognostic signatures, each of them related to a specific cancer type, to generate a unique pan-cancer prognostic signature, that contains 207 unique probesets related to 187 unique gene symbols, with one particular probeset present in two cancer type-specific signatures (203072_at related to the MYO1E gene). We applied our proposed pan-cancer signature with the Random Forests machine learning method to 57 microarray gene expression datasets of 12 different cancer types, and analyzed the results. We also compared the performance of our pan-cancer signature with the performances of two alternative prognostic signatures, and with the performances of each cancer type-specific signature on their corresponding cancer type-specific datasets. Our results confirmed the effectiveness of our prognostic pan-cancer signature. Moreover, we performed a pathway enrichment analysis, which indicated an association between the signature genes and a protein-protein interaction analysis, that highlighted PIK3R2 and FN1 as key genes having a fundamental relevance in our signature, suggesting an important role in pan-cancer prognosis for both of them.

Collagen Family as Promising Biomarkers and Therapeutic Targets in Cancer

Despite advances in cancer detection and therapy, it has been estimated that the incidence of cancers will increase, while the mortality rate will continue to remain high, a fact explained by the large number of patients diagnosed in advanced stages when therapy is often useless. Therefore, it is necessary to invest knowledge and resources in the development of new non-invasive biomarkers for the early detection of cancer and new therapeutic targets for better health management. In this review, we provided an overview on the collagen family as promising biomarkers and on how they may be exploited as therapeutic targets in cancer. The collagen family tridimensional structure, organization, and functions are very complex, being in a tight relationship with the extracellular matrix, tumor, and immune microenvironment. Moreover, accumulating evidence underlines the role of collagens in promoting tumor growth and creating a permissive tumor microenvironment for metastatic dissemination. Knowledge of the molecular basis of these interactions may help in cancer diagnosis and prognosis, in overcoming chemoresistance, and in providing new targets for cancer therapies.

COL11A1 as a potential prognostic target for oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is a malignant tumor occurring in the oral cavity. However, the molecular mechanism of OSCC is not clear. Bioinformatics was used to screen and identify role of collagen type X1 alpha 1 (COL11A1) on OSCC. 200 patients with OSCC were recruited. Clinical and follow-up data were recorded and COL11A1 expression levels were tested. Pearson chi-square test and Spearman correlation coefficient were used to analyze relationship between prognosis and related parameters in patients with OSCC. Univariate and multivariate Logistic regression, univariate and multivariate Cox proportional risk regression were used for further analysis, survival curve was drawn. Through bioinformatics analysis, OSCC patients with higher expression of COL11A1 have poor overall survival compare with OSCC patients with lower expression of COL11A1 (hazard ratios [HR] = 1.32, P = .047). Pearson chi-square test showed that age (P = .011), tumor grade (P = .023), COL11A1 (P < .001) was significantly correlated with prognosis of OSCC. Univariate Logistic regression analysis showed age (odds ratio [OR] = 2.102, 95% confidence intervals [95%CI]: 1.180-3.746, P = .012), tumor grade (OR = 1.919, 95%CI: 1.093-3.372, P = .023) and COL11A1 (OR = 12.775, 95%CI: 6.509-25.071, P < .001). Multivariate Logistic regression analysis showed that COL11A1 (OR = 12.066, 95%CI: 6.042-24.096, P < .001) was significantly associated with prognosis of patients with OSCC. Univariate Cox regression analysis showed that age (HR = 1.592, 95%CI: 1.150-2.205, P = .005), tumor grade (HR = 1.460, 95%CI: 1.067-1.999, P = .018) and COL11A1 (HR = 1.848, 95%CI: 1.340-2.548, P < .001) were significantly correlated with survival time of OSCC patients. Multivariate Cox regression analysis showed that tumor grade (HR = 1.466, 95%CI: 1.064-2.020, P = .019) and COL11A1 (HR = 1.645, 95%CI: 1.164-2.325, P = .005) were significantly correlated with survival time of OSCC patients. COL11A1 is significantly correlated with occurrence of OSCC. When COL11A1 is highly expressed, prognosis of patients with OSCC is worse and the survival time is shorter.

Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data

Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor.

Collagen Type XI Inhibits Lung Cancer-Associated Fibroblast Functions and Restrains the Integrin Binding Site Availability on Collagen Type I Matrix

The tumor microenvironment, including cancer-associated fibroblast (CAF), plays an active role in non-small cell lung cancer (NSCLC) development and progression. We previously reported that collagen type XI and integrin α11, a collagen receptor, were upregulated in NSCLC; the latter promotes tumor growth and metastasis. We here explored the role of collagen type XI in NSCLC stroma. We showed that the presence of collagen type XI in collagen type I matrices inhibits CAF-mediated collagen remodeling and cell migration. This resulted in the inhibition of CAF-dependent lung-tumor cell invasion. Among the collagen receptors expressed on CAF, we determined that DDR2 and integrin α2β1, but not integrin α11β1, mediated the high-affinity binding to collagen type XI. We further demonstrated that collagen type XI restrained the integrin binding site availability on collagen type I matrices, thus limiting cell interaction with collagen type I. As a consequence, CAFs failed to activate FAK, p38 and Akt one hour after they interacted with collagen type I/XI. We concluded that collagen type XI may have a competitive negative feedback role on the binding of collagen type I to its receptors.

Cancer-associated fibroblasts: Origin, function, imaging, and therapeutic targeting

The tumor microenvironment (TME) is emerging as one of the primary barriers in cancer therapy. Cancer-associated fibroblasts (CAF) are a common inhabitant of the TME in several tumor types and play a critical role in tumor progression and drug resistance via different mechanisms such as desmoplasia, angiogenesis, immune modulation, and cancer metabolism. Due to their abundance and significance in pro-tumorigenic mechanisms, CAF are gaining attention as a diagnostic target as well as to improve the efficacy of cancer therapy by their modulation. In this review, we highlight existing imaging techniques that are used for the visualization of CAF and CAF-induced fibrosis and provide an overview of compounds that are known to modulate CAF activity. Subsequently, we also discuss CAF-targeted and CAF-modulating nanocarriers. Finally, our review addresses ongoing challenges and provides a glimpse into the prospects that can spearhead the transition of CAF-targeted therapies from opportunity to reality.

Human Papillary and Reticular Fibroblasts Show Distinct Functions on Tumor Behavior in 3D-Organotypic Cultures Mimicking Melanoma and HNSCC

Human dermis can be morphologically divided into the upper papillary and lower reticular dermis. Previously, we demonstrated that papillary (PFs) and reticular (RFs) fibroblasts show distinct morphology and gene expression profiles. Moreover, they differently affect tumor invasion and epithelial-to-mesenchymal transition (EMT) in in vitro 3D-organotypic cultures of cutaneous squamous cell carcinoma (cSCC). In this study, we examined if these distinct effects of PFs and RFs can be extrapolated in other epithelial/non-epithelial tumors such as melanoma and head and neck squamous cell carcinoma (HNSCC). To this end, 3D-Full-Thickness Models (FTMs) were established from melanoma (AN and M14) or HNSCC cell lines (UM-SCC19 and UM-SCC47) together with either PFs or RFs in the dermis. The interplay between tumor cells and different fibroblasts was investigated. We observed that all the tested tumor cell lines showed significantly stronger invasion in RF-FTMs compared to PF-FTMs. In addition, RF-FTMs demonstrated more tumor cell proliferation, EMT induction and basement membrane disruption. Interestingly, RFs started to express the cancer-associated fibroblast (CAF) biomarker α-SMA, indicating reciprocal interactions eventuating in the transition of RFs to CAFs. Collectively, in the melanoma and HNSCC FTMs, interaction of RFs with tumor cells promoted EMT and invasion, which was accompanied by differentiation of RFs to CAFs.

Cancer-Associated Fibroblasts: Tumorigenicity and Targeting for Cancer Therapy

Simple Summary

Cancer-associated fibroblasts (CAFs) are found in the tumor microenvironment and exhibit several protumorigenic functions. Preclinical studies suggest that CAFs can be reduced, eliminated, or reprogrammed; however, clinical translation has not yet occurred. A better understanding of these cells and their functions will undoubtedly improve cancer treatments. In this review, we summarize current research, highlight major challenges, and discuss future opportunities for improving our knowledge of CAF biology and targeting.

Abstract

Cancer-associated fibroblasts (CAFs) are a heterogenous group of activated fibroblasts and a major component of the tumor stroma. CAFs may be derived from fibroblasts, epithelial cells, endothelial cells, cancer stem cells, adipocytes, pericytes, or stellate cells. These complex origins may underlie their functional diversity, which includes pro-tumorigenic roles in extracellular matrix remodeling, the suppression of anti-tumor immunity, and resistance to cancer therapy. Several methods for targeting CAFs to inhibit tumor progression and enhance anti-tumor immunity have recently been reported. While preclinical studies have shown promise, to date they have been unsuccessful in human clinical trials against melanoma, breast cancer, pancreas cancer, and colorectal cancers. This review summarizes recent and major advances in CAF-targeting therapies, including DNA-based vaccines, anti-CAF CAR-T cells, and modifying and reprogramming CAF functions. The challenges in developing effective anti-CAF treatment are highlighted, which include CAF heterogeneity and plasticity, the lack of specific target markers for CAFs, the limitations in animal models recapitulating the human cancer microenvironment, and the undesirable off-target and systemic side effects. Overcoming these challenges and expanding our understanding of the basic biology of CAFs is necessary for making progress towards safe and effective therapeutic strategies against cancers in human patients.

Computational pathology in ovarian cancer

Histopathologic evaluations of tissue sections are key to diagnosing and managing ovarian cancer. Pathologists empirically assess and integrate visual information, such as cellular density, nuclear atypia, mitotic figures, architectural growth patterns, and higher-order patterns, to determine the tumor type and grade, which guides oncologists in selecting appropriate treatment options. Latent data embedded in pathology slides can be extracted using computational imaging. Computers can analyze digital slide images to simultaneously quantify thousands of features, some of which are visible with a manual microscope, such as nuclear size and shape, while others, such as entropy, eccentricity, and fractal dimensions, are quantitatively beyond the grasp of the human mind. Applications of artificial intelligence and machine learning tools to interpret digital image data provide new opportunities to explore and quantify the spatial organization of tissues, cells, and subcellular structures. In comparison to genomic, epigenomic, transcriptomic, and proteomic patterns, morphologic and spatial patterns are expected to be more informative as quantitative biomarkers of complex and dynamic tumor biology. As computational pathology is not limited to visual data, nuanced subvisual alterations that occur in the seemingly “normal” pre-cancer microenvironment could facilitate research in early cancer detection and prevention. Currently, efforts to maximize the utility of computational pathology are focused on integrating image data with other -omics platforms that lack spatial information, thereby providing a new way to relate the molecular, spatial, and microenvironmental characteristics of cancer. Despite a dire need for improvements in ovarian cancer prevention, early detection, and treatment, the ovarian cancer field has lagged behind other cancers in the application of computational pathology. The intent of this review is to encourage ovarian cancer research teams to apply existing and/or develop additional tools in computational pathology for ovarian cancer and actively contribute to advancing this important field.

LINC00665/miRNAs axis-mediated collagen type XI alpha 1 correlates with immune infiltration and malignant phenotypes in lung adenocarcinoma

Collagen type XI alpha 1 (COL11A1) as an oncogene has been reported in several malignant tumors. Herein, we aimed to explore the function of COL11A1 and its upstream regulators in lung adenocarcinoma (LUAD). COL11A1 expression prognostic significance, gene ontology, Kyoto Encyclopedia of Genes and Genomes, and immune infiltration were explored in LUAD. In vitro experimental measurements were implemented to validate the function of COL11A1 and LINC00665 in LUAD cells. Our study demonstrated that LINC00665-2 and COL11A1 were significantly upregulated in LUAD tissues compared with nontumor tissues. COL11A1 was positively correlated with multiple immune cell enrichment, suggesting that COL11A1 may be a prospective therapeutic target to enhance the efficacy of immunotherapy in LUAD. A regulatory mechanism LINC00665-2/microRNAs (miRNAs)/COL11A1 axis was identified to facilitate the tumorigenesis of LUAD. si-LINC00665 transfection induced the inhibition of growth and migration, and apoptosis was reversed by the overexpression of COL11A1 in LUAD cells. In conclusion, LINC00665 as a competing endogenous RNA sponging multiple miRNAs to modulate COL11A1 expression in LUAD, suggesting that LINC00665/miRNAs/COL11A1 axis may contribute to the pathogenesis of LUAD.

Collagen XI Alpha 1 Chain, a Novel Therapeutic Target for Cancer Treatment

The extracellular matrix (ECM) plays an important role in the progression of cancer. Collagen is the most abundant component in ECM, and is involved in the biological formation of cancer. Although type XI collagen is a minor fibrillar collagen, collagen XI alpha 1 chain (COL11A1) expression has been found to be upregulated in a variety of human cancers including colorectal, esophagus, glioma, gastric, head and neck, lung, ovarian, pancreatic, salivary gland, and renal cancers. High levels of COL11A1 usually predict poor prognosis, owing to its association with angiogenesis, invasion, and drug resistance in cancer. However, little is known about the specific mechanism through which COL11A1 regulates tumor progression. Here, we have organized and summarized recent developments regarding the interactions between COL11A1 and intracellular signaling pathways and selected therapeutic agents targeting COL11A1, as these indicate its potential as a target for treatment of cancers, especially epithelial ovarian cancer.

Mutually Exclusive Expression of COL11A1 by CAFs and Tumour Cells in a Large panCancer and a Salivary Gland Carcinoma Cohort

Procollagen 11A1 (COL11A1) is a central component of the extracellular matrix in many carcinomas, which is considered to be mainly produced by cancer associated fibroblasts (CAFs). As COL11A1 expression correlates with adverse prognosis and is implicated in chemoresistance, it is a promising putative target. For the first time, we used RNA in-situ hybridization to systematically identify the cells that produce COL11A1 in the ten most prevalent carcinoma types, lymphomas (n = 275) and corresponding normal tissue (n = 55; panCancer cohort). Moreover, as most salivary gland carcinomas (SGC) display distinct stromal architectures, we also analysed 110 SGC. The corresponding protein formation of COL11A1 was determined by MALDI-TOF-MS-Imaging. We report that colon, breast and salivary duct carcinomas are highly infiltrated by COL11A1 positive CAFs (CAFs_COL11A1) and might thus be promising candidates for antidesmoplastic or COL11A1-targeted therapies. The amount of CAFs_COL11A1 correlated significantly with tumour grade, tumour stage and nodal spread in the panCancer cohort. Significant associations between CAFs_COL11A1 and vascular invasion, perineural spread and nodal spread were observed in the SGC cohort. Also, we discovered that tumour cells of intercalated duct derived SGC and CAFs produce COL11A1 in a mutually exclusive manner. Our findings represent a novel mode of extracellular matrix production in carcinomas and could be highly relevant in the future. Our findings elucidate the mode of COL11A1 expression in very different carcinoma types and may aid to categorise tumours in the setting of possible future COL11A1-related therapies.

Perivascular Fibrosis Is Mediated by a KLF10-IL-9 Signaling Axis in CD4+ T Cells

BACKGROUND

Perivascular fibrosis, characterized by increased amount of connective tissue around vessels, is a hallmark for vascular disease. Ang II (angiotensin II) contributes to vascular disease and end-organ damage via promoting T-cell activation. Despite recent data suggesting the role of T cells in the progression of perivascular fibrosis, the underlying mechanisms are poorly understood.

METHODS

TF (transcription factor) profiling was performed in peripheral blood mononuclear cells of hypertensive patients. CD4-targeted KLF10 (Kruppel like factor 10)-deficient (Klf10^fl/flCD4^Cre+; [TKO]) and CD4-Cre (Klf10^+/+CD4^Cre+; (Cre)) control mice were subjected to Ang II infusion. End point characterization included cardiac echocardiography, aortic imaging, multiorgan histology, flow cytometry, cytokine analysis, aorta and fibroblast transcriptomic analysis, and aortic single-cell RNA-sequencing.

RESULTS

TF profiling identified increased KLF10 expression in hypertensive human subjects and in CD4+ T cells in Ang II-treated mice. TKO mice showed enhanced perivascular fibrosis, but not interstitial fibrosis, in aorta, heart, and kidney in response to Ang II, accompanied by alterations in global longitudinal strain, arterial stiffness, and kidney function compared with Cre control mice. However, blood pressure was unchanged between the 2 groups. Mechanistically, KLF10 bound to the IL (interleukin)-9 promoter and interacted with HDAC1 (histone deacetylase 1) inhibit IL-9 transcription. Increased IL-9 in TKO mice induced fibroblast intracellular calcium mobilization, fibroblast activation, and differentiation and increased production of collagen and extracellular matrix, thereby promoting the progression of perivascular fibrosis and impairing target organ function. Remarkably, injection of anti-IL9 antibodies reversed perivascular fibrosis in Ang II-infused TKO mice and C57BL/6 mice. Single-cell RNA-sequencing revealed fibroblast heterogeneity with activated signatures associated with robust ECM (extracellular matrix) and perivascular fibrosis in Ang II-treated TKO mice.

CONCLUSIONS

CD4+ T cell deficiency of Klf10 exacerbated perivascular fibrosis and multi-organ dysfunction in response to Ang II via upregulation of IL-9. Klf10 or IL-9 in T cells might represent novel therapeutic targets for treatment of vascular or fibrotic diseases.

Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients

BACKGROUND

Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only "curative" treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC.

METHODS

In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database.

RESULTS

LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19.

CONCLUSIONS

In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs.

Collagen XI Alpha 1 (COL11A1) Expression in the Tumor Microenvironment Drives Neuroblastoma Dissemination

BACKGROUND

Neuroblastoma (NB) is among the most common cancers in children. A highly aggressive form of cancer, NB relies on cells in the microenvironment for dissemination particularly cancer associated fibroblast (CAFs). CAFs synthesise the extracellular matrix to create a scaffold for tumor growth thus enabling the carcinogenesis of NB, Collagen, an abundant scaffold protein produced by CAFs, has been implicated in the creation of an optimal tumor microenvironment, however, the expression profile of collagen within NB is not yet known.

METHODS

We characterised collagen expression within the tumor-stroma boundary by microarray and confirmed by qRT-PCR and immunohistochemistry.

RESULTS

The collagen marker, COL11A1, was also upregulated in NB CD45+ cells and SMA+ CAFs. Furthermore, SMA+ CAFs led to neuroblastoma cell invasion in an in vitro co-culture system which was subsequently attenuated by gene silencing COL11A1. Immunohistochemical staining of clinical tumor samples revealed that high COL11A1 expression in the stroma adjacent to tumour site, significantly associated with advanced cancer stages, age ≥18 months, undifferentiated tumor status, relapse and poor overall survival.

CONCLUSION

Collectively, these results suggest that a COL11A1 signature in the NB microenvironment could represent a novel target for therapeutic intervention.

Somatic mutations in collagens are associated with a distinct tumor environment and overall survival in gastric cancer

Background

Gastric cancer is a heterogeneous disease with poorly understood genetic and microenvironmental factors. Mutations in collagen genes are associated with genetic diseases that compromise tissue integrity, but their role in tumor progression has not been extensively reported. Aberrant collagen expression has been long associated with malignant tumor growth, invasion, chemoresistance, and patient outcomes. We hypothesized that somatic mutations in collagens could functionally alter the tumor extracellular matrix.

Methods

We used publicly available datasets including The Tumor Cancer Genome Atlas (TCGA) to interrogate somatic mutations in collagens in stomach adenocarcinomas. To demonstrate that collagens were significantly mutated above background mutation rates, we used a moderated Kolmogorov-Smirnov test along with combination analysis with a bootstrap approach to define the background accounting for mutation rates. Association between mutations and clinicopathological features was evaluated by Fisher or chi-squared tests. Association with overall survival was assessed by Kaplan-Meier and the Cox-Proportional Hazards Model. Gene Set Enrichment Analysis was used to interrogate pathways. Immunohistochemistry and in situ hybridization tested expression of COL7A1 in stomach tumors.

Results

In stomach adenocarcinomas, we identified individual collagen genes and sets of collagen genes harboring somatic mutations at a high frequency compared to background in both microsatellite stable, and microsatellite instable tumors in TCGA. Many of the missense mutations resemble the same types of loss of function mutations in collagenopathies that disrupt tissue formation and destabilize cells providing guidance to interpret the somatic mutations. We identified combinations of somatic mutations in collagens associated with overall survival, with a distinctive tumor microenvironment marked by lower matrisome expression and immune cell signatures. Truncation mutations were strongly associated with improved outcomes suggesting that loss of expression of secreted collagens impact tumor progression and treatment response. Germline collagenopathy variants guided interpretation of impactful somatic mutations on tumors.

Conclusions

These observations highlight that many collagens, expressed in non-physiologically relevant conditions in tumors, harbor impactful somatic mutations in tumors, suggesting new approaches for classification and therapy development in stomach cancer. In sum, these findings demonstrate how classification of tumors by collagen mutations identified strong links between specific genotypes and the tumor environment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09136-1.

Identification of key tumor stroma-associated transcriptional signatures correlated with survival prognosis and tumor progression in breast cancer

BACKGROUND

The aberrant expression of stromal gene signatures in breast cancer has been widely studied. However, the association of stromal gene signatures with tumor immunity, progression, and clinical outcomes remains lacking.

METHODS

Based on eight breast tumor stroma (BTS) transcriptomics datasets, we identified differentially expressed genes (DEGs) between BTS and normal breast stroma. Based on the DEGs, we identified dysregulated pathways and prognostic hub genes, hub oncogenes, hub protein kinases, and other key marker genes associated with breast cancer. Moreover, we compared the enrichment levels of stromal and immune signatures between breast cancer patients with bad and good clinical outcomes. We also investigated the association between tumor stroma-related genes and breast cancer progression.

RESULTS

The DEGs included 782 upregulated and 276 downregulated genes in BTS versus normal breast stroma. The pathways significantly associated with the DEGs included cytokine-cytokine receptor interaction, chemokine signaling, T cell receptor signaling, cell adhesion molecules, focal adhesion, and extracellular matrix-receptor interaction. Protein-protein interaction network analysis identified the stromal hub genes with prognostic value in breast cancer, including two oncogenes (COL1A1 and IL21R), two protein kinases encoding genes (PRKACA and CSK), and a growth factor encoding gene (PLAU). Moreover, we observed that the patients with bad clinical outcomes were less enriched in stromal and antitumor immune signatures (CD8 + T cells and tumor-infiltrating lymphocytes) but more enriched in tumor cells and immunosuppressive signatures (MDSCs and CD4 + regulatory T cells) compared with the patients with good clinical outcomes. The ratios of CD8 + /CD4 + regulatory T cells were lower in the patients with bad clinical outcomes. Furthermore, we identified the tumor stroma-related genes, including MCM4, SPECC1, IMPA2, and AGO2, which were gradually upregulated through grade I, II, and III breast cancers. In contrast, COL14A1, ESR1, SLIT2, IGF1, CH25H, PRR5L, ABCA6, CEP126, IGDCC4, LHFP, MFAP3, PCSK5, RAB37, RBMS3, SETBP1, and TSPAN11 were gradually downregulated through grade I, II, and III breast cancers. It suggests that the expression of these stromal genes has an association with the progression of breast cancers. These progression-associated genes also displayed an expression association with recurrence-free survival in breast cancer patients.

CONCLUSIONS

This study identified tumor stroma-associated biomarkers correlated with deregulated pathways, tumor immunity, tumor progression, and clinical outcomes in breast cancer. Our findings provide new insights into the pathogenesis of breast cancer.

The Functional Role of Extracellular Matrix Proteins in Cancer

The extracellular matrix (ECM) is highly dynamic as it is constantly deposited, remodeled and degraded to maintain tissue homeostasis. ECM is a major structural component of the tumor microenvironment, and cancer development and progression require its extensive reorganization. Cancerized ECM is biochemically different in its composition and is stiffer compared to normal ECM. The abnormal ECM affects cancer progression by directly promoting cell proliferation, survival, migration and differentiation. The restructured extracellular matrix and its degradation fragments (matrikines) also modulate the signaling cascades mediated by the interaction with cell-surface receptors, deregulate the stromal cell behavior and lead to emergence of an oncogenic microenvironment. Here, we summarize the current state of understanding how the composition and structure of ECM changes during cancer progression. We also describe the functional role of key proteins, especially tenascin C and fibronectin, and signaling molecules involved in the formation of the tumor microenvironment, as well as the signaling pathways that they activate in cancer cells.

Bioinformatics Tools to Understand Notch

As a result of the culmination of data, and the fast-paced advancement of new research, all the biological information collected can make it difficult to sort data. This is oftentimes experienced when learning about the human genome. Fortunately, with the advancement of technology, the field of bioinformatics has emerged which has allowed for the creation of a variety of biological databases. These biological databases provide a condensed reservoir of organized information that is easy to use and topic-specific. Here, we provide a list of 39 biological databases that help break down the fundamental details of a gene. This chapter uses the NOTCH1 gene as an example to demonstrate how biological databases can be used to extract gene information. Five sections were created to highlight the major areas needed to build a comprehensive foundation of NOTCH1. The first section lists databases containing basic gene and protein product information. The next section consists of protein interactions and signaling pathway databases which are essential in understanding the biological processes a gene product is involved in. Gene expression and disease databases are the next two sections which are connected since disease results from the aberrant expression of a gene product. The last database section examines model organisms which serve a key role in the study of human genetic diseases. Using these databases, we can elucidate NOTCH1's gene/protein structure, expression, and vital physiological function through the Notch signaling pathway.

Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data

The extracellular matrix (ECM) has historically been explored through proteomic methods. Whether or not global transcriptomics can yield meaningful information on the human matrisome is unknown. Gene expression data from 17,382 samples across 52 tissues, were obtained from the Genotype-Tissue Expression (GTEx) project. Additional datasets were obtained from The Cancer Genome Atlas (TCGA) program and the Gene Expression Omnibus for comparisons. Gene expression levels generally matched proteome-derived matrisome expression patterns. Further, matrisome gene expression properly clustered tissue types, with some matrisome genes including SERPIN family members having tissue-restricted expression patterns. Deeper analyses revealed 382 gene transcripts varied by age and 315 varied by sex in at least one tissue, with expression correlating with digitally imaged histologic tissue features. A comparison of TCGA tumor, TCGA adjacent normal and GTEx normal tissues demonstrated robustness of the GTEx samples as a generalized matrix control, while also determining a common primary tumor matrisome. Additionally, GTEx tissues served as a useful non-diseased control in a separate study of idiopathic pulmonary fibrosis (IPF) matrix changes, while identifying 22 matrix genes upregulated in IPF. Altogether, these findings indicate that the transcriptome, in general, and GTEx in particular, has value in understanding the state of organ ECM.

The role of cell surface proteins gene expression in diagnosis, prognosis, and drug resistance of colorectal cancer: In silico analysis and validation

Cell surface proteins (CSPs) are an important type of protein in different essential cell functions. This study aimed to distinguish overexpressed CSPs in colorectal cancer to investigate their biomarker, prognosis, and drug resistance potential. Raw data of three datasets including 1187 samples was downloaded then normalization and differential expression were performed. By the combination of the cancer genome atlas (TCGA) clinical data, survival analysis was carried out. Information of all CSPs was collected from cell surface protein atlas. The role of each candidate gene expression was investigated in drug resistance by CCEL and GDSC data from PharmacoGX. CRC samples including 30 tumor samples and adjacent normal were used to confirm data by RT-qPCR. Outcomes showed that 66 CSPs overexpressed in three datasets, and 146 CSPs expression associated with poor prognosis features in TCGA data that TIMP1 and QSOX2 can associate with poor patient survival independently. High-risk patients illustrated more fatality than low-risk patients based on the risk score calculated by the expression level of these genes. Receiver operating characteristic curve analysis showed that 39 CSPs as perfect biomarkers for diagnosis in CRC. Furthermore, QSOX2 and TIMP1 expression levels increased in tumor samples compared to adjacent normal samples. The Drug resistance analysis demonstrated ADAM12 and COL1A2 up-regulation among 66 overexpressed CSPs caused resistance to Venetoclax and Cyclophosphamide with a high estimate, respectively. Many CSPs are deregulated in CRC, and can be valuable candidates as biomarkers for diagnosis, prognosis, and drug resistance.

Engineering stromal heterogeneity in cancer

Based on our exponentially increasing knowledge of stromal heterogeneity from advances in single-cell technologies, the notion that stromal cell types exist as a spectrum of unique subpopulations that have specific functions and spatial distributions in the tumor microenvironment has significant impact on tumor modeling for drug development and personalized drug testing. In this Review, we discuss the importance of incorporating stromal heterogeneity and tumor architecture, and propose an overall approach to guide the reconstruction of stromal heterogeneity in vitro for tumor modeling. These next-generation tumor models may support the development of more precise drugs targeting specific stromal cell subpopulations, as well as enable improved recapitulation of patient tumors in vitro for personalized drug testing.

Extensive three-dimensional intratumor proteomic heterogeneity revealed by multiregion sampling in high-grade serous ovarian tumor specimens

Enriched tumor epithelium, tumor-associated stroma, and whole tissue were collected by laser microdissection from thin sections across spatially separated levels of ten high-grade serous ovarian carcinomas (HGSOCs) and analyzed by mass spectrometry, reverse phase protein arrays, and RNA sequencing. Unsupervised analyses of protein abundance data revealed independent clustering of an enriched stroma and enriched tumor epithelium, with whole tumor tissue clustering driven by overall tumor "purity." Comparing these data to previously defined prognostic HGSOC molecular subtypes revealed protein and transcript expression from tumor epithelium correlated with the differentiated subtype, whereas stromal proteins (and transcripts) correlated with the mesenchymal subtype. Protein and transcript abundance in the tumor epithelium and stroma exhibited decreased correlation in samples collected just hundreds of microns apart. These data reveal substantial tumor microenvironment protein heterogeneity that directly bears on prognostic signatures, biomarker discovery, and cancer pathophysiology and underscore the need to enrich cellular subpopulations for expression profiling.

Single-cell analysis reveals the pan-cancer invasiveness-associated transition of adipose-derived stromal cells into COL11A1-expressing cancer-associated fibroblasts

During the last ten years, many research results have been referring to a particular type of cancer-associated fibroblasts associated with poor prognosis, invasiveness, metastasis and resistance to therapy in multiple cancer types, characterized by a gene expression signature with prominent presence of genes COL11A1, THBS2 and INHBA. Identifying the underlying biological mechanisms responsible for their creation may facilitate the discovery of targets for potential pan-cancer therapeutics. Using a novel computational approach for single-cell gene expression data analysis identifying the dominant cell populations in a sequence of samples from patients at various stages, we conclude that these fibroblasts are produced by a pan-cancer cellular transition originating from a particular type of adipose-derived stromal cells naturally present in the stromal vascular fraction of normal adipose tissue, having a characteristic gene expression signature. Focusing on a rich pancreatic cancer dataset, we provide a detailed description of the continuous modification of the gene expression profiles of cells as they transition from APOD-expressing adipose-derived stromal cells to COL11A1-expressing cancer-associated fibroblasts, identifying the key genes that participate in this transition. These results also provide an explanation to the well-known fact that the adipose microenvironment contributes to cancer progression.

Profiling Cancer-Associated Fibroblasts in Melanoma

Solid tumors are complex systems characterized by dynamic interactions between neoplastic cells, non-tumoral cells, and extracellular components. Among all the stromal cells that populate tumor microenvironment, fibroblasts are the most abundant elements and are critically involved in disease progression. Cancer-associated fibroblasts (CAFs) have pleiotropic functions in tumor growth and extracellular matrix remodeling implicated in local invasion and distant metastasis. CAFs additionally participate in the inflammatory response of the tumor site by releasing a variety of chemokines and cytokines. It is becoming clear that understanding the dynamic, mutual melanoma-fibroblast relationship would enable treatment options to be amplified. To better characterize melanoma-associated fibroblasts, here we analyzed low-passage primary CAFs derived from advanced-stage primary skin melanomas, focusing on the immuno-phenotype. Furthermore, we assessed the expression of several CAF markers and the production of growth factors. To deepen the study of CAF-melanoma cell crosstalk, we employed CAF-derived supernatants and trans-well co-culture systems to evaluate the influences of CAFs on (i) the motogenic ability of melanoma cells, (ii) the chemotherapy-induced cytotoxicity, and (iii) the release of mediators active in modulating tumor growth and spread.

Modelling TGFβR and Hh pathway regulation of prognostic matrisome molecules in ovarian cancer

In a multi-level "deconstruction" of omental metastases, we previously identified a prognostic matrisome gene expression signature in high-grade serous ovarian cancer (HGSOC) and twelve other malignancies. Here, our aim was to understand how six of these extracellular matrix (ECM) molecules, COL11A1, cartilage oligomeric matrix protein, FN1, versican, cathepsin B, and COL1A1, are upregulated in cancer. Using biopsies, we identified significant associations between TGFβR activity, Hedgehog (Hh) signaling, and these ECM molecules and studied the associations in mono-, co-, and tri-culture. Activated omental fibroblasts (OFs) produced more matrix than malignant cells, directed by TGFβR and Hh signaling cross talk. We "reconstructed" omental metastases in tri-cultures of HGSOC cells, OFs, and adipocytes. This combination was sufficient to generate all six ECM proteins and the matrisome expression signature. TGFβR and Hh inhibitor combinations attenuated fibroblast activation and gel and ECM remodeling in these models. The tri-culture model reproduces key features of omental metastases and allows study of diseased-associated ECM.

Activation of COL11A1 by PRRX1 promotes tumor progression and radioresistance in ovarian cancer

PURPOSE

Although radiotherapy is a common treatment option for all kinds of cancer patients, including ovarian cancer, a major obstacle limiting its application in the development of resistance. Therefore, it is urgently needed to clarify the mechanism of radiosensitivity modulation.

MATERIALS AND METHODS

We obtained open datasets and analyzed the expression of collagen type XI alpha 1 (COL11A1) in ovarian cancer patients with different stages. Meanwhile, the correlation of COL11A1 and survival outcomes is determined by Kaplan-Meier analysis. The role of COL11A1 in cell proliferation was observed in an in vitro knockdown system. SKOV3 radioresistant cells were established to determine the role of COL11A1 on radioresistant in ovarian cancer.

RESULTS AND DISCUSSION

COL11A1 were highly enriched in late-stage ovarian cancer tumor tissues and negatively correlated with survival outcomes in ovarian cancer. The functional analysis found that COL11A1 promoted ovarian cancer cell proliferation in vitro. Importantly, COL11A1 decreased radiosensitivity in ovarian cancer by AKT activation. Paired related homeobox 1 (PRRX1) acted as an upstream transcription factor to regulate COL11A1 expression in ovarian cancer. Increased COL11A1 expression is related to low survival outcomes and radiosensitivity in ovarian cancer.

CONCLUSIONS

Targeting COL11A1 is a promising strategy for improving radiotherapy efficiency.

Cancer-associated fibroblast migration in non-small cell lung cancers is modulated by increased integrin α11 expression

Cancer‐associated fibroblasts (CAFs) regulate cancer progression through the modulation of extracellular matrix (ECM) and cancer cell adhesion. While undergoing a series of phenotypic changes, CAFs control cancer–stroma interactions through integrin receptor signaling. Here, we isolated CAFs from patients with non‐small‐cell lung cancer (NSCLC) and examined their gene expression profiles. We identified collagen type XI α1 (COL11A1), integrin α11 (ITGA11), and the ITGA11 major ligand collagen type I α1 (COL1A1) among the 390 genes that were significantly enriched in NSCLC‐associated CAFs. Increased ITGA11 expression in cancer stroma was correlated with a poor clinical outcome in patients with NSCLC. Increased expression of fibronectin and collagen type I induced ITGA11 expression in CAFs. The cellular migration of CAFs toward collagen type I and fibronectin was promoted via ERK1/2 signaling, independently of the fibronectin receptor integrin α5β1. Additionally, ERK1/2 signaling induced ITGA11 and COL11A1 expression in cancer stroma. We, therefore, propose that targeting ITGA11 and COL11A1 expressing CAFs to block cancer–stroma interactions may serve as a novel, promising anti‐tumor strategy.

The Burden of Post-Translational Modification (PTM)-Disrupting Mutations in the Tumor Matrisome

BACKGROUND

To evaluate the occurrence of mutations affecting post-translational modification (PTM) sites in matrisome genes across different tumor types, in light of their genomic and functional contexts and in comparison with the rest of the genome.

METHODS

This study spans 9075 tumor samples and 32 tumor types from The Cancer Genome Atlas (TCGA) Pan-Cancer cohort and identifies 151,088 non-silent mutations in the coding regions of the matrisome, of which 1811 affecting known sites of hydroxylation, phosphorylation, N- and O-glycosylation, acetylation, ubiquitylation, sumoylation and methylation PTM.

RESULTS

PTM-disruptive mutations (PTMmut) in the matrisome are less frequent than in the rest of the genome, seem independent of cell-of-origin patterns but show dependence on the nature of the matrisome protein affected and the background PTM types it generally harbors. Also, matrisome PTMmut are often found among structural and functional protein regions and in proteins involved in homo- and heterotypic interactions, suggesting potential disruption of matrisome functions.

CONCLUSIONS

Though quantitatively minoritarian in the spectrum of matrisome mutations, PTMmut show distinctive features and damaging potential which might concur to deregulated structural, functional, and signaling networks in the tumor microenvironment.

Collagen Type XI Alpha 1 (COL11A1): A Novel Biomarker and a Key Player in Cancer

Collagen type XI alpha 1 (COL11A1), one of the three alpha chains of type XI collagen, is crucial for bone development and collagen fiber assembly. Interestingly, COL11A1 expression is increased in several cancers and high levels of COL11A1 are often associated with poor survival, chemoresistance, and recurrence. This review will discuss the recent discoveries in the biological functions of COL11A1 in cancer. COL11A1 is predominantly expressed and secreted by a subset of cancer-associated fibroblasts, modulating tumor-stroma interaction and mechanical properties of extracellular matrix. COL11A1 also promotes cancer cell migration, metastasis, and therapy resistance by activating pro-survival pathways and modulating tumor metabolic phenotype. Several inhibitors that are currently being tested in clinical trials for cancer or used in clinic for other diseases, can be potentially used to target COL11A1 signaling. Collectively, this review underscores the role of COL11A1 as a promising biomarker and a key player in cancer.

Exploring the Differential Expression and Prognostic Significance of the COL11A1 Gene in Human Colorectal Carcinoma: An Integrated Bioinformatics Approach

Colorectal cancer is one of the most common cancers of humans and the second highest in cancer-related death. Genes used as prognostic biomarkers play an imperative role in cancer detection and may direct the development of appropriate therapeutic strategies. Collagen type XI alpha 1 (COL11A1) is a minor fibrillary collagen that has an essential role in the regulation of cell division, differentiation, proliferation, migration, growth, and apoptosis of intestinal and colon cells. The present study seeks to evaluate the significance of the COL11A1 gene in the progression of colorectal cancer in humans across the various parameters using advanced bioinformatics approaches. The application of various databases and servers like ONCOMINE, UALCAN, and GEPIA were accessed for analyzing the differential expression of the COLL11A1 gene and its relative influence over the survival of the transformed subjects. In addition, oncogenomics of COL11A1 gene, mutations associated with this gene and interacting partners of the gene in the context of oncogenesis were studied using COSMIC, cBioPortal, GeneMANIA, and NetworkAnalyst. Our experimental data indicate that the COL11A1 gene is overexpressed in the transformed tissues across the various clinicopathological parameters reduces the probability of survival in both overall and disease-specific survival cases. Mutational studies imply that it can induce perturbations in various signaling pathways viz. RTK-RAS-PI3K, Wnt, TGF-β, and TP53 pathways influencing cancer development. Also, a positive association and correlation amongst the THBS2, COL10A1, COL5A2, and COL1A2 genes were observed, which most likely to contribute to the upregulation of carcinogenesis. Conclusively, this comprehensive study indicates the COL11A1 gene to be a significant contributor in the etiology of colorectal cancer, henceforth this gene can be considered as a prognostic biomarker for the conception of diagnostic and therapeutic strategies against colorectal cancer in the near future.

Human cutaneous neurofibroma matrisome revealed by single-cell RNA sequencing

Neurofibromatosis Type I (NF1) is a neurocutaneous genetic syndrome characterized by a wide spectrum of clinical presentations, including benign peripheral nerve sheath tumor called neurofibroma. These tumors originate from the Schwann cell lineage but other cell types as well as extracellular matrix (ECM) in the neurofibroma microenvironment constitute the majority of the tumor mass. In fact, collagen accounts for up to 50% of the neurofibroma's dry weight. Although the presence of collagens in neurofibroma is indisputable, the exact repertoire of ECM genes and ECM-associated genes (i.e. the matrisome) and their functions are unknown. Here, transcriptome profiling by single-cell RNA sequencing reveals the matrisome of human cutaneous neurofibroma (cNF). We discovered that classic pro-fibrogenic collagen I myofibroblasts are rare in neurofibroma. In contrast, collagen VI, a pro-tumorigenic ECM, is abundant and mainly secreted by neurofibroma fibroblasts. This study also identified potential cell type-specific markers to further elucidate the biology of the cNF microenvironment.

Mutant collagen COL11A1 enhances cancerous invasion

Collagens are the most abundant proteins in the body and comprise the basement membranes and stroma through which cancerous invasion occurs; however, a pro-neoplastic function for mutant collagens is undefined. Here we identify COL11A1 mutations in 66 of 100 cutaneous squamous cell carcinomas (cSCCs), the second most common U.S. cancer, concentrated in a triple helical region known to produce trans-dominant collagens. Analysis of COL11A1 and other collagen genes found that they are mutated across common epithelial malignancies. Knockout of mutant COL11A1 impairs cSCC tumorigenesis in vivo. Compared to otherwise genetically identical COL11A1 wild-type tissue, gene-edited mutant COL11A1 skin is characterized by induction of β1 integrin targets and accelerated neoplastic invasion. In mosaic tissue, mutant COL11A1 cells enhanced invasion by neighboring wild-type cells. These results suggest that specific collagens are commonly mutated in cancer and that mutant collagens may accelerate this process.

Bizarre giant cells in human angiosarcoma exhibit chemoresistance and contribute to poor survival outcomes

Giant cells (GC) are a poorly understood subset of tumor cells that have been increasingly recognized as a potential contributor to tumor heterogeneity and treatment resistance. We aimed to characterize the biological and clinical significance of GC in angiosarcoma, an aggressive rare cancer of endothelial origin. Archival angiosarcoma samples were examined for the presence of GC and compared with clinicopathological as well as NanoString gene expression data. GC were examined in angiosarcoma cell lines MOLAS and ISOHAS using conventional and electron microscopy, single cell whole genome profiling, and other assays. In the cell lines, GC represented a rare population of mitotically active, non–senescent CD31⁺ cells, and shared similar genomic profiles with regular‐sized cells, consistent with a malignant endothelial phenotype. GC remained viable and persisted in culture following exposure to paclitaxel and doxorubicin. In patient samples, GC were present in 24 of 58 (41.4%) cases. GC was correlated with poorer responses to chemotherapy (25.0% vs 73.3%, P = 0.0213) and independently contributed to worse overall survival outcomes (hazard ratio 2.20, 95% confidence interval 1.17‐4.15, P = 0.0142). NanoString profiling revealed overexpression of genes, including COL11A1, STC1, and ERO1A, accompanied by upregulation of immune‐related metabolic stress and metastasis/matrix remodeling pathways in GC‐containing tumors. In conclusion, GC may contribute to chemoresistance and poor prognosis in angiosarcoma.

Collagen-rich omentum is a premetastatic niche for integrin α2-mediated peritoneal metastasis

The extracellular matrix (ECM) plays critical roles in tumor progression and metastasis. However, the contribution of ECM proteins to early metastatic onset in the peritoneal cavity remains unexplored. Here, we suggest a new route of metastasis through the interaction of integrin alpha 2 (ITGA2) with collagens enriched in the tumor coinciding with poor outcome in patients with ovarian cancer. Using multiple gene-edited cell lines and patient-derived samples, we demonstrate that ITGA2 triggers cancer cell adhesion to collagen, promotes cell migration, anoikis resistance, mesothelial clearance, and peritoneal metastasis in vitro and in vivo. Mechanistically, phosphoproteomics identify an ITGA2-dependent phosphorylation of focal adhesion kinase and mitogen-activated protein kinase pathway leading to enhanced oncogenic properties. Consequently, specific inhibition of ITGA2-mediated cancer cell-collagen interaction or targeting focal adhesion signaling may present an opportunity for therapeutic intervention of metastatic spread in ovarian cancer.

lncRNA small nucleolar RNA host gene 12 promotes renal cell carcinoma progression by modulating the miR‑200c‑5p/collagen type XI α1 chain pathway

Renal cell carcinoma (RCC) is a primary malignant kidney cancer subtype. It has been suggested that long non-coding RNAs (lncRNAs) serve important roles in the progression of kidney cancer. In fact, the lncRNA small nucleolar RNA host gene 12 (SNHG12) was discovered to be overexpressed in various types of cancer. However, to the best of our knowledge, the role of SNHG12 in RCC remains unclear. The present study aimed to investigate the function of SNHG12 and its underlying molecular mechanism of action in RCC. In patient samples and datasets from The Cancer Genome Atlas. Reverse transcription-quantitative PCR, demonstrated that SNHG12 expression levels were upregulated in RCC tumor tissues, but not in normal kidney tissues. SNHG12 upregulation was also observed in RCC cell lines. Kaplan-Meier survival analysis indicated a poor prognosis for those patients with RCC who had upregulated SNHG12 expression levels. Following lentivirus transduction, SNHG12 was successfully knocked down (validated by western blot analysis) and cell migration and invasion assays were performed. SNHG12 knockdown markedly inhibited cell viability and invasion, while increasing apoptosis in both A498 and 786O cell lines. The results of the luciferase reporter assay suggested that SNHG12 exerted its role by sponging microRNA (miR)-200c-5p, which led to the upregulation of its target gene, collagen type XI α1 chain (COL11A1). This was further validated, as miR-200c-5p inhibition reduced the effects of SNHG12 downregulation on cell viability and apoptosis, without affecting SNHG12 expression levels. Furthermore, the findings indicated that SNHG12 may partially exert its role through COL11A1, which was also upregulated in RCC. In conclusion, the results of the present study suggested that the SNHG12/miR-200c-5p/COL11A1 axis may be crucial for RCC progression, which provided an insight into potential therapeutic strategies for RCC treatment.

Expression Profiling of Extracellular Matrix Genes Reveals Global and Entity-Specific Characteristics in Adenoid Cystic, Mucoepidermoid and Salivary Duct Carcinomas

Simple Summary

The extracellular matrix (ECM), an important factor in tumour metastasis and therapy resistance, has not been studied in salivary gland carcinomas (SGC), so far. In this retrospective study, we profiled the RNA expression of 28 ECM-related genes in 11 adenoid cystic (AdCy), 14 mucoepidermoid (MuEp) and 9 salivary duct carcinomas (SaDu). Also, we validated our results in a multimodal approach. MuEp and SaDu shared a common gene signature involving an overexpression of COL11A1. In contrast, nonhierarchical clustering revealed a more specific gene expression pattern for AdCy, characterized by overexpression of COL27A1. In situ studies at RNA level indicated that in AdCy, ECM production results from tumour cells and not from cancer-associated fibroblasts as is the case in MuEp and SaDu. For the first time, we characterized the ECM composition in SGC and identified several differentially expressed genes, which are potential therapeutic targets.

Abstract

The composition of the extracellular matrix (ECM) plays a pivotal role in tumour initiation, metastasis and therapy resistance. Until now, the ECM composition of salivary gland carcinomas (SGC) has not been studied. We quantitatively analysed the mRNA of 28 ECM-related genes of 34 adenoid cystic (AdCy; n = 11), mucoepidermoid (MuEp; n = 14) and salivary duct carcinomas (SaDu; n = 9). An incremental overexpression of six collagens (including COL11A1) and four glycoproteins from MuEp and SaDu suggested a common ECM alteration. Conversely, AdCy and MuEp displayed a distinct overexpression of COL27A1 and LAMB3, respectively. Nonhierarchical clustering and principal component analysis revealed a more specific pattern for AdCy with low expression of the common gene signature. In situ studies at the RNA and protein level confirmed these results and indicated that, in contrast to MuEp and SaDu, ECM production in AdCy results from tumour cells and not from cancer-associated fibroblasts (CAFs). Our findings reveal different modes of ECM production leading to common and distinct RNA signatures in SGC. Of note, an overexpression of COL27A1, as in AdCy, has not been linked to any other neoplasm so far. Here, we contribute to the dissection of the ECM composition in SGC and identified a panel of deferentially expressed genes, which could be putative targets for SGC therapy and overcoming therapeutic resistance.

Reciprocal Interplay Between Fibrillar Collagens and Collagen-Binding Integrins: Implications in Cancer Progression and Metastasis

Cancers are complex ecosystems composed of malignant cells embedded in an intricate microenvironment made of different non-transformed cell types and extracellular matrix (ECM) components. The tumor microenvironment is governed by constantly evolving cell-cell and cell-ECM interactions, which are now recognized as key actors in the genesis, progression and treatment of cancer lesions. The ECM is composed of a multitude of fibrous proteins, matricellular-associated proteins, and proteoglycans. This complex structure plays critical roles in cancer progression: it functions as the scaffold for tissues organization and provides biochemical and biomechanical signals that regulate key cancer hallmarks including cell growth, survival, migration, differentiation, angiogenesis, and immune response. Cells sense the biochemical and mechanical properties of the ECM through specialized transmembrane receptors that include integrins, discoidin domain receptors, and syndecans. Advanced stages of several carcinomas are characterized by a desmoplastic reaction characterized by an extensive deposition of fibrillar collagens in the microenvironment. This compact network of fibrillar collagens promotes cancer progression and metastasis, and is associated with low survival rates for cancer patients. In this review, we highlight how fibrillar collagens and their corresponding integrin receptors are modulated during cancer progression. We describe how the deposition and alignment of collagen fibers influence the tumor microenvironment and how fibrillar collagen-binding integrins expressed by cancer and stromal cells critically contribute in cancer hallmarks.