Identification of stromal ColXα1 and tumor-infiltrating lymphocytes as putative predictive markers of neoadjuvant therapy in estrogen receptor-positive/HER2-positive breast cancer

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

Tumor collagens predict genetic features and patient outcomes

The extracellular matrix (ECM) is a critical determinant of tumor fate that reflects the output from myriad cell types in the tumor. Collagens constitute the principal components of the tumor ECM. The changing collagen composition in tumors along with their impact on patient outcomes and possible biomarkers remains largely unknown. The RNA expression of the 43 collagen genes from solid tumors in The Cancer Genome Atlas (TCGA) was clustered to classify tumors. PanCancer analysis revealed how collagens by themselves can identify the tissue of origin. Clustering by collagens in each cancer type demonstrated strong associations with survival, specific immunoenvironments, somatic gene mutations, copy number variations, and aneuploidy. We developed a machine learning classifier that predicts aneuploidy, and chromosome arm copy number alteration (CNA) status based on collagen expression alone with high accuracy in many cancer types with somatic mutations, suggesting a strong relationship between the collagen ECM context and specific molecular alterations. These findings have broad implications in defining the relationship between cancer-related genetic defects and the tumor microenvironment to improve prognosis and therapeutic targeting for patient care, opening new avenues of investigation to define tumor ecosystems.

Prognostic value of COL10A1 and its correlation with tumor-infiltrating immune cells in urothelial bladder cancer: A comprehensive study based on bioinformatics and clinical analysis validation

Introduction

Bladder cancer (BLCA) is one of the most lethal diseases. COL10A1 is secreted small-chain collagen in the extracellular matrix associated with various tumors, including gastric, colon, breast, and lung cancer. However, the role of COL10A1 in BLCA remains unclear. This is the first research focusing on the prognostic value of COL10A1 in BLCA. In this research, we aimed to uncover the association between COL10A1 and the prognosis, as well as other clinicopathological parameters in BLCA.

Methods

We obtained gene expression profiles of BLCA and normal tissues from the TCGA, GEO, and ArrayExpress databases. Immunohistochemistry staining was performed to investigate the protein expression and prognostic value of COL10A1 in BLCA patients. GO and KEGG enrichment along with GSEA analyses were performed to reveal the biological functions and potential regulatory mechanisms of COL10A1 based on the gene co-expression network. We used the “maftools” R package to display the mutation profiles between the high and low COL10A1 groups. GIPIA2, TIMER, and CIBERSORT algorithms were utilized to explore the effect of COL10A1 on the tumor immune microenvironment.

Results

We found that COL10A1 was upregulated in the BLCA samples, and increased COL10A1 expression was related to poor overall survival. Functional annotation of 200 co-expressed genes positively correlated with COL10A1 expression, including GO, KEGG, and GSEA enrichment analyses, indicated that COL10A1 was basically involved in the extracellular matrix, protein modification, molecular binding, ECM-receptor interaction, protein digestion and absorption, focal adhesion, and PI3K-Akt signaling pathway. The most commonly mutated genes of BLCA were different between high and low COL10A1 groups. Tumor immune infiltrating analyses showed that COL10A1 might have an essential role in recruiting infiltrating immune cells and regulating immunity in BLCA, thus affecting prognosis. Finally, external datasets and biospecimens were used, and the results further validated the aberrant expression of COL10A1 in BLCA samples.

Conclusions

In conclusion, our study demonstrates that COL10A1 is an underlying prognostic and predictive biomarker in BLCA.

COL10A1-DDR2 axis promotes the progression of pancreatic cancer by regulating MEK/ERK signal transduction

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignant tumors with a poor prognosis. Type X collagen α 1 chain (COL10A1), a member of the collagen family, is a gene associated with the progression of a variety of human tumors, but the specific function and molecular mechanism of COL10A1 in pancreatic cancer remain unclear. Our study found that COL10A1 is highly expressed in pancreatic cancer cells and tissues, and its high expression is related to poor prognosis and some clinicopathological features, such as tumor size and differentiation. Biological functional experiments showed that overexpression of COL10A1 enhanced the proliferation and migration of PDAC cells. Interestingly, discoid protein domain receptor 2 (DDR2), the receptor of COL10A1, is regulated by COL10A1. We found that the COL10A1-DDR2 axis activates the mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) pathway, which leads to epithelial-mesenchymal transformation (EMT) and accelerates the progression of pancreatic cancer. In summary, COL10A1 regulates PDAC cell proliferation and MEK/ERK signaling pathways by binding to DDR2 to promote migration, invasion and EMT. Our study suggested that COL10A1 might be a critical factor in promoting PDAC progression. More research is needed to confirm COL10A1 as a potential biomarker and therapeutic target for PDAC.

Association between genome-wide epigenetic and genetic alterations in breast cancer tissue and response to HER2-targeted therapies in HER2-positive breast cancer patients: new findings and a systematic review

Recent evidence suggests that genetic and epigenetic mechanisms might be associated with acquired resistance to cancer therapies. The aim of this study was to assess the association of genome-wide genetic and epigenetic alterations with the response to anti-HER2 agents in HER2-positive breast cancer patients. PubMed was screened for articles published until March 2021 on observational studies investigating the association of genome-wide genetic and epigenetic alterations, measured in breast cancer tissues or blood, with the response to targeted treatment in HER2-positive breast cancer patients. Sixteen studies were included in the review along with ours, in which we compared the genome-wide DNA methylation pattern in breast tumor tissues of patients who acquired resistance to treatment (case group, n = 6) to that of patients who did not develop resistance (control group, n = 6). Among genes identified as differentially methylated between the breast cancer tissue of cases and controls, one of them, PRKACA, was also reported as differentially expressed in two studies included in the review. Although included studies were heterogeneous in terms of methodology and study population, our review suggests that genes of the PI3K pathway may play an important role in developing resistance to anti-HER2 agents in breast cancer patients. Genome-wide genetic and epigenetic alterations measured in breast cancer tissue or blood might be promising markers of resistance to anti-HER2 agents in HER2-positive breast cancer patients. Further studies are needed to confirm these data.

High COL10A1 expression potentially contributes to poor outcomes in gastric cancer with the help of LEF1 and Wnt2

Background

COL10A1 is a secreted, short‐chain collagen found in several types of cancer. Studies have shown that COL10A1 aberrant expression is considered an oncogenic factor. However, its underlying mechanisms and regulation of gastric cancer remain undefined.

Methods

The data on the expression of COL10A1, clinicopathological characteristics, and outcome of patients with GC were obtained from The Cancer Genome Atlas. The ALGGEN‐PROMO database defined the related transcription factors. Quantitative real‐time reverse transcription‐polymerase chain reaction and western blotting analysis were used to identify the differential expression levels of COL10A1 and related transcription factors.

Results

We found that high COL10A1 expression is an independent risk factor for gastric cancer. Upregulation of LEF1 and Wnt2 was also observed in gastric cancer, suggesting a potential correlation between LEF1/COL10A1 regulation in the Wnt2 signaling pathway.

Conclusion

High COL10A1 expression may contribute to poor outcomes via upregulation of LEF1 and Wnt2 in gastric cancer.

The role of network-forming collagens in cancer progression

Collagens are the main components of extracellular matrix in the tumor microenvironment. Both fibrillar and nonfibrillar collagens are involved in tumor progression. The nonfibrillar network-forming collagens such as type IV and type VIII collagens are frequently overexpressed in various types of human cancers, which promotes tumor cell proliferation, adhesion, invasion, metastasis and angiogenesis. Studies on the roles of these collagens have shed light on the mechanisms underpinning the effects of this protein family. Future research has to explicit the role of network-forming collagens with respect to cancer progression and treatment. Herein, we review the regulation of network-forming collagens expression in cancer; the roles of network-forming collagens in tumor invasion, metastasis and angiogenesis; and the clinical significance of network-forming collagens expression in cancer patients. This article is protected by copyright. All rights reserved.

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.

In Situ Overexpression of Matricellular Mechanical Proteins Demands Functional Immune Signature and Mitigates Non-Small Cell Lung Cancer Progression

Non-small cell lung carcinoma (NSCLC) is a complex cancer biome composed of malignant cells embedded in a sophisticated tumor microenvironment (TME) combined with different initiating cell types, including immune cells and cancer-associated fibroblasts (CAFs), and extracellular matrix (ECM) proteins. However, little is known about these tumors’ immune-matricellular relationship as functional and mechanical barriers. This study investigated 120 patients with NSCLC to describe the immune-matricellular phenotypes of their TME and their relationship with malignant cells. Immunohistochemistry (IHC) was performed to characterize immune checkpoints (PD-L1, LAG-3, CTLA-4+, VISTA 1), T cells (CD3+), cytotoxic T cells (CD8⁺, Granzyme B), macrophages (CD68+), regulatory T cells (FOXP3+, CD4+), natural killer cells (CD57+), and B lymphocytes (CD20+), whereas CAFs and collagen types I, III, and V were characterized by immunofluorescence (IF). We observed two distinct functional immune-cellular barriers—the first of which showed proximity between malignant cells and cytotoxic T cells, and the second of which showed distant proximity between non-cohesive nests of malignant cells and regulatory T cells. We also identified three tumor-associated matricellular barriers: the first, with a localized increase in CAFs and a low deposition of Col V, the second with increased CAFs, Col III and Col I fibers, and the third with a high amount of Col fibers and CAFs bundled and aligned perpendicularly to the tumor border. The Cox regression analysis was designed in two steps. First, we investigated the relationship between the immune-matricellular components and tumor pathological stage (I, II, and IIIA), and better survival rates were seen in patients whose tumors expressed collagen type III > 24.89 fibers/mm². Then, we included patients who had progressed to pathological stage IV and found an association between poor survival and tumor VISTA 1 expression > 52.86 cells/mm² and CD3+ ≤ 278.5 cells/mm². We thus concluded that differential patterns in the distribution of immune-matricellular phenotypes in the TME of NSCLC patients could be used in translational studies to predict new treatment strategies and improve patient outcome. These data raise the possibility that proteins with mechanical barrier function in NSCLC may be used by cancer cells to protect them from immune cell infiltration and immune-mediated destruction, which can otherwise be targeted effectively with immunotherapy or collagen therapy.

Estrogen/ER in anti-tumor immunity regulation to tumor cell and tumor microenvironment

As the essential sexual hormone, estrogen and its receptor has been proved to participate in the regulation of autoimmunity diseases and anti-tumor immunity. The adjustment of tumor immunity is related to the interaction between cancer cells, immune cells and tumor microenvironment, all of which is considered as the potential target in estrogen-induced immune system regulation. However, the specific mechanism of estrogen-induced immunity is poorly understood. Typically, estrogen causes the nuclear localization of estrogen/estrogen receptor complex and alternates the transcription pattern of target genes, leading to the reprogramming of tumor cells and differentiation of immune cells. However, the estrogen-induced non-canonical signal pathway activation is also crucial to the rapid function of estrogen, such as NF-κB, MAPK-ERK, and β-catenin pathway activation, which has not been totally illuminated. So, the investigation of estrogen modulatory mechanisms in these two manners is vital for the tumor immunity and can provide the potential for endocrine hormone targeted cancer immunotherapy. Here, this review summarized the estrogen-induced canonical and non-canonical signal transduction pathway and aimed to focus on the relationship among estrogen and cancer immunity as well as immune-related tumor microenvironment regulation. Results from these preclinical researches elucidated that the estrogen-target therapy has the application prospect of cancer immunotherapy, which requires the further translational research of these treatment strategies.

Current trends in the treatment of HR+/HER2+ breast cancer

Treatment for HR+/HER2+ patients has been debated, as some tumors within this luminal HER2+ subtype behave like luminal A cancers, whereas others behave like non-luminal HER2+ breast cancers. Recent research and clinical trials have revealed that a combination of hormone and targeted anti-HER2 approaches without chemotherapy provides long-term disease control for at least some HR+/HER2+ patients. Novel anti-HER2 therapies, including neratinib and trastuzumab emtansine, and new agents that are effective in HR+ cancers, including the next generation of oral selective estrogen receptor downregulators/degraders and CDK4/6 inhibitors such as palbociclib, are now being evaluated in combination. This review discusses current trials and results from previous studies that will provide the basis for current recommendations on how to treat newly diagnosed patients with HR+/HER2+ disease.

Bioinformatics analysis of prognostic significance of COL10A1 in breast cancer

Background: Collagen type X alpha 1 (COL10A1) is overexpressed in diverse tumors and displays vital roles in tumorigenesis. However, the prognostic value of COL10A1 in breast cancer remains unclear.

Methods: The expression of COL10A1 was analyzed by the Oncomine database and UALCAN cancer database. The relationship between COL10A1 expression level and clinical indicators including prognostic data in breast cancer were analyzed by the Kaplan–Meier Plotter, PrognoScan, and Breast Cancer Gene-Expression Miner (bc-GenExMiner) databases.

Results: COL10A1 was up-regulated in different subtypes of breast cancer. Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2) status and nodal status were positively correlated with COL10A1 expression. Conversely, age, the Scarff–Bloom–Richardson (SBR) grade, basal-like status, and triple-negative status were negatively related to COL10A1 level in breast cancer samples compared with normal tissues. Patients with increased COL10A1 expression level showed worse overall survival (OS), relapse-free survival (RFS), distant metastasis-free survival (DMFS) and disease-free survival (DFS). COL10A1 was positively correlated with metastatic relapse-free survival. GSEA analysis revealed that enrichment of TGF-β signaling pathway. 15-leucine-rich repeat containing membrane protein (LRRC15) is a correlated gene of COL10A1.

Conclusion: Bioinformatics analysis revealed that COL10A1 might be considered as a predictive biomarker for prognosis of breast cancer. Further experiments and clinical trials are essential to elucidate the value of COL10A1 in breast cancer treatment.

Upregulated Collagen COL10A1 Remodels the Extracellular Matrix and Promotes Malignant Progression in Lung Adenocarcinoma

Collagens are major components of the ECM in various organs, including the lungs. Ectopic expression of collagens can regulate the tumor progression and disease outcome through remodeling of the extracellular matrix (ECM). However, it remains largely unexplored whether collagens are involved in the tumor progression of lung adenocarcinoma (LUAD). Analysis of three LUAD transcriptional expression profiles showed that COL10A1 mRNA expression was up-regulated and associated with poor prognosis. Gain- and loss-of-function studies were performed to observe that up-regulated COL10A1 promotes LUAD cell proliferation and invasion in vitro and in vivo. In molecular mechanism study, we found that COL10A1 interacts with DDR2 and affects the downstream FAK signaling pathway to regulate LUAD cell progression. The expression of COL10A1 on tissue microarray (TMA) was also measured to explore the association between COL10A1 expression and patient outcome. The results addressed that COL10A1 is up-regulated and positively correlated with lymph node metastasis in lung adenocarcinoma, and the COL10A1 expression is also an independent prognostic factor. In summary, the up-regulated COL10A1 remodels the ECM and the COL10A1/DDR2/FAK axis regulates the proliferation and metastasis of LUAD cells, implying that COL10A1 is a promising therapeutic target and prognostic marker for LUAD patients.

Predictive and prognostic role of tumour-infiltrating lymphocytes in breast cancer patients with different molecular subtypes: a meta-analysis

BACKGROUND

Whether tumour-infiltrating lymphocytes (TILs) play different roles in different molecular subtypes of breast cancer remains unknown. Additionally, their prognostic and predictive value in different molecular subtypes of breast cancer is still controversial. The aim of our meta-analysis was to assess the prognostic and predictive value of TILs in different molecular subtypes of breast cancer by summarizing all relevant studies performing multivariate analysis.

METHODS

PubMed, Embase, EBSCO, ScienceDirect, the Cochrane Database and Web of Science were comprehensively searched (until March 2020). Hazard ratios (HRs), odds ratios (ORs) and their 95% confidence intervals (CIs) were used as effect measures to perform our meta-analysis. A random effect model was used. Stata software, version 15 (2017) (StataCorp, College Station, TX, USA) was used to perform the statistical analysis.

RESULTS

Thirty-three studies including 18,170 eligible breast cancer patients were analysed. The meta-analysis showed that high TIL expression was significantly associated with increased pathological complete response (pCR) rates after neoadjuvant chemotherapy in patients with the HER2-enriched molecular subtype (OR = 1.137, 95% CI [1.061 ~ 1.218], p < 0.001) and triple-negative breast cancer (TNBC) subtype (OR = 1.120, 95% CI [1.061 ~ 1.182], p < 0.001). However, high TIL expression was not significantly associated with high pCR rates after neoadjuvant chemotherapy in patients with the luminal molecular subtype of breast cancer (OR = 1.154, 95% CI [0.789 ~ 1.690], p = 0.460). We carried out a meta-analysis on the HRs of overall survival (OS) and disease-free survival (DFS) to assess the prognostic value of TILs in breast cancer with different molecular subtypes more deeply. Our meta-analysis confirmed that high TILs were associated with significantly improved DFS in patients with the HER2-enriched molecular subtype [HR = 0.940, 95% CI (0.903 ~ 0.979), p = 0.003] and TNBC molecular subtype [HR = 0.907, 95% CI (0.862 ~ 0.954), p < 0.001]. However, high TILs were not associated with significantly better DFS in patients with the luminal molecular subtype of breast cancer [HR = 0.998, 95% CI (0.977 ~ 1.019), p = 0.840]. Furthermore, the results confirmed that high TILs were significantly related to better OS in patients with the HER2-enriched molecular subtype [HR = 0.910, 95% CI (0.866 ~ 0.957), p < 0.001] and TNBC molecular subtype [HR = 0.869, 95% CI (0.836 ~ 0.904), p < 0.001]. Conversely, the summarized results indicated that high TILs were significantly associated with poor OS in patients with the luminal molecular subtype of breast cancer [HR = 1.077, 95% CI (1.016 ~ 1.141), p = 0.012].

CONCLUSIONS

Our meta-analysis confirms that high TILs are associated with favourable survival and predicts pCR in breast cancer patients with the TNBC and HER2-enriched molecular subtypes.

High plasma levels of COL10A1 are associated with advanced tumor stage in gastric cancer patients

BACKGROUND

Gastric cancer (GC) remains an aggressive malignancy with a high rate of mortality, being the third leading cause of cancer-related death. More than one million newly diagnosed cases and 782685 deaths due to GC were reported in 2018. GC is characterized by limited effective treatment options and the lack of consistent biomarkers for the diagnosis and prognosis of these patients. The discovery of new biomarkers useful in the early diagnosis of GC is mandatory.

AIM

To evaluate the potential of COL10A1 as a circulating biomarker for the diagnosis and prognosis of gastric adenocarcinoma patients.

METHODS

Plasma and tissue obtained from 49 patients with gastric adenocarcinoma have been used in exploring the expression of COL10A1. Real-time PCR and western blot techniques were used to evaluate COL10A1 level in gastric tumor tissue compared to normal adjacent tissue. The circulating level of COL10A1 was also evaluated by ELISA in plasma of gastric adenocarcinoma patients. Survival analysis was made in order to evaluate the potential of COL10A1 as a biomarker for the diagnosis and prognosis of gastric adenocarcinoma patients.

RESULTS

Our results showed a significant increase in COL10A1 gene expression and protein levels in gastric tumor tissue compared to adjacent normal tissue (P < 0.05). COL10A1 seems to show an elevated expression from the beginning of carcinogenesis, in the early stages, and its increased level remains elevated during cancer progression. A significant increase of COL10A1 plasma level in gastric adenocarcinoma patients was also identified. Moreover, increased COL10A1 plasma level was associated with poor survival of the patients. Plasma COL10A1 performed a diagnostic value in GC with area under the receiver operating characteristic curve (AUC) of 0.9171 (P = 0.0002), sensitivity of 87.76%, and specificity of 100.0%. Furthermore, this study demonstrated the potential role of plasma COL10A1 in the early detection of GC, as in the early stage, we obtained an AUC of 0.8789 (P = 0.0030), sensitivity of 81.25%, and specificity of 100.0%.

CONCLUSION

Circulating expression level of COL10A1 is significantly increased in gastric adenocarcinoma patients being associated with poor survival and is a potential biomarker for early detection of GC.

Predictions for high COL1A1 and COL10A1 expression resulting in a poor prognosis in esophageal squamous cell carcinoma by bioinformatics analyses

Background

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignant neoplasms of the digestive tract worldwide. The lack of key molecular biomarkers is associated with the poor prognosis in ESCC patients. The present study was aimed to identify candidate genes for diagnostic, prognostic, and therapeutic applications in ESCC by bioinformatics.

Methods

Two datasets of ESCC (GSE20347 and GSE70409) from gene expression omnibus (GEO) were analyzed using GEO2R online tool to identify the differentially expressed genes (DEGs). Subsequently, functions and pathways enrichment analyses of DEGs and their protein-protein interaction (PPI) network analyses were performed. When key DEGs were identified, their relationship with ESCC prognosis was further validated.

Results

There were 134 commonly changed DEGs (33 up-regulated and 101 down-regulated) from GSE20347 and GSE70409 datasets were identified using integrated bioinformatical analysis. Gene ontology (GO) and pathway enrichment analysis was performed to annotate genes and gene products, highlight biological processes (BPs) and systemic functional information. Through the PPI network and cluster analysis, two clusters containing 21 key DEGs were detected and 14 of them were validated based on TCGA and GTEx data. Among these key DEGs, COL1A1 and COL10A1 were significantly associated with the prognosis in ESCC cases.

Conclusions

In conclusion, a total of 14 key DEGs and outcome in ESCC were identified by integrated bioinformatics analyses. COL1A1 and COL10A1 might be novel potential diagnostic and prognostic biomarkers in ESCC.

Elastin in the Tumor Microenvironment

Elastic fibers are found in the extracellular matrix (ECM) of tissues requiring resilience and depend on elasticity. Elastin and its degradation products have multiple roles in the oncologic process. In many malignancies, the remodeled ECM expresses high levels of the elastin protein which may have either positive or negative effects on tumor growth. Elastin cross-linking with other ECM components and the enzymes governing this process all have effects on tumorigenesis. Elastases, and specifically neutrophil elastase, are key drivers of invasion and metastasis and therefore are important targets for inhibition. Elastin degradation leads to the generation of bioactive fragments and elastin-derived peptides that further modulate tumor growth and spread. Interestingly, elastin-like peptides (ELP) and elastin-derived peptides (EDP) may also be utilized as nano-carriers to combat tumor growth. EDPs drive tumor development in a variety of ways, and specifically targeting EDPs and their binding proteins are major objectives for ongoing and future anti-cancer therapies. Research on both the direct anti-cancer activity and the drug delivery capabilities of ELPs is another area likely to result in novel therapeutic agents in the near future.

NRSN2 promotes breast cancer metastasis by activating PI3K/AKT/mTOR and NF-κB signaling pathways

Breast cancer is a leading cause of cancer-associated mortality globally amongst gynecologic tumors due to aggressive metastasis. A previous study reported that neurensin-2 (NRSN2) was implicated in human cancer cells, and that NRSN2 gene and protein expression levels were significantly upregulated in human breast cancer tissues compared with adjacent non-tumor tissues. The purpose of the present study was to analyze the role of NRSN2 in the metastasis of breast cancer cells and explore its potential mechanism. Reverse transcription-quantitative PCR, MTT, western blotting and immunohistochemistry was used to analyze the role of NRSN2 both in vitro and in vivo. The present study demonstrated that NRSN2 knockdown inhibited the proliferation, migration and invasion of breast cancer cells in vitro. NRSN2 upregulation promoted breast cancer cell proliferation and tissue growth in vitro and in vivo. In addition, the results demonstrated that the regulatory effects of NRSN2 on breast cancer cells were associated with PI3K/AKT/mTOR and NF-κB signaling pathway dysregulation. Furthermore, NRSN2 overexpression in mice significantly promoted breast cancer cell proliferation. In conclusion, the results from the present study indicated that NRSN2 may be considered as a novel oncogenic protein and may represent a potential therapeutic target for breast cancer.

Stromal ColXα1 expression correlates with tumor-infiltrating lymphocytes and predicts adjuvant therapy outcome in ER-positive/HER2-positive breast cancer

Background

The breast cancer microenvironment contributes to tumor progression and response to chemotherapy. Previously, we reported that increased stromal Type X collagen α1 (ColXα1) and low TILs correlated with poor pathologic response to neoadjuvant therapy in estrogen receptor and HER2-positive (ER+/HER2+) breast cancer. Here, we investigate the relationship of ColXα1 and long-term outcome of ER+/HER2+ breast cancer patients in an adjuvant setting.

Methods

A total of 164 cases with at least 5-year follow-up were included. Immunohistochemistry for ColXα1 was performed on whole tumor sections. Associations between ColXα1expression, clinical pathological features, and outcomes were analyzed.

Results

ColXα1 expression was directly proportional to the amount of tumor associated stroma (p = 0.024) and inversely proportional to TILs. Increased ColXα1 was significantly associated with shorter disease free survival and overall survival by univariate analysis. In multivariate analysis, OS was lower in ColXα1 expressing (HR = 2.1; 95% CI = 1.2–3.9) tumors of older patients (> = 58 years) (HR = 5.3; 95% CI = 1.7–17) with higher stage (HR = 2.6; 95% CI = 1.3–5.2). Similarly, DFS was lower in ColXα1 expressing (HR = 1.8; 95% CI = 1.6–5.7) tumors of older patients (HR = 3.2; 95% CI = 1.3–7.8) with higher stage (HR = 2.7; 95% CI = 1.6–5.7) and low TILs. In low PR+ tumors, higher ColXα1 expression was associated with poorer prognosis.

Conclusion

ColXα1 expression is associated with poor disease free survival and overall survival in ER+/HER2+ breast cancer. This study provides further support for the prognostic utility of ColXα1 as a breast cancer associated stromal factor that predicts response to chemotherapy.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-6134-y) contains supplementary material, which is available to authorized users.

The role of collagen in cancer: from bench to bedside

Collagen is the major component of the tumor microenvironment and participates in cancer fibrosis. Collagen biosynthesis can be regulated by cancer cells through mutated genes, transcription factors, signaling pathways and receptors; furthermore, collagen can influence tumor cell behavior through integrins, discoidin domain receptors, tyrosine kinase receptors, and some signaling pathways. Exosomes and microRNAs are closely associated with collagen in cancer. Hypoxia, which is common in collagen-rich conditions, intensifies cancer progression, and other substances in the extracellular matrix, such as fibronectin, hyaluronic acid, laminin, and matrix metalloproteinases, interact with collagen to influence cancer cell activity. Macrophages, lymphocytes, and fibroblasts play a role with collagen in cancer immunity and progression. Microscopic changes in collagen content within cancer cells and matrix cells and in other molecules ultimately contribute to the mutual feedback loop that influences prognosis, recurrence, and resistance in cancer. Nanoparticles, nanoplatforms, and nanoenzymes exhibit the expected gratifying properties. The pathophysiological functions of collagen in diverse cancers illustrate the dual roles of collagen and provide promising therapeutic options that can be readily translated from bench to bedside. The emerging understanding of the structural properties and functions of collagen in cancer will guide the development of new strategies for anticancer therapy.

Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer

Background

Exploration of the genes with abnormal expression during the development of breast cancer is essential to provide a deeper understanding of the mechanisms involved. Transcriptome sequencing and bioinformatics analysis of invasive ductal carcinoma and paracancerous tissues from the same patient were performed to identify the key genes and signaling pathways related to breast cancer development.

Methods

Samples of breast tumor tissue and paracancerous breast tissue were obtained from 6 patients. Sequencing used the Illumina HiSeq platform. All. Only perfectly matched clean reads were mapped to the reference genome database, further analyzed and annotated based on the reference genome information. Differentially expressed genes (DEGs) were identified using the DESeq R package (1.10.1) and DEGSeq R package (1.12.0). Using KOBAS software to execute the KEGG bioinformatics analyses, enriched signaling pathways of DEGs involved in the occurrence of breast cancer were determined. Subsequently, quantitative real time PCR was used to verify the accuracy of the expression profile of key DEGs from the RNA-seq result and to explore the expression patterns of novel cancer-related genes on 8 different clinical individuals.

Results

The transcriptomic sequencing results showed 937 DEGs, including 487 upregulated and 450 downregulated genes in the breast cancer specimens. Further quantitative gene expression analysis was performed and captured 252 DEGs (201 downregulated and 51 upregulated) that showed the same differential expression pattern in all libraries. Finally, 6 upregulated DEGs (CST2, DRP2, CLEC5A, SCD, KIAA1211, DTL) and 6 downregulated DEGs (STAC2, BTNL9, CA4, CD300LG, GPIHBP1 and PIGR), were confirmed in a quantitative real time PCR comparison of breast cancer and paracancerous breast tissues from 8 clinical specimens. KEGG analysis revealed various pathway changes, including 20 upregulated and 21 downregulated gene enrichment pathways. The extracellular matrix–receptor (ECM-receptor) interaction pathway was the most enriched pathway: all genes in this pathway were DEGs, including the THBS family, collagen and fibronectin. These DEGs and the ECM-receptor interaction pathway may perform important roles in breast cancer.

Conclusion

Several potential breast cancer-related genes and pathways were captured, including 7 novel upregulated genes and 76 novel downregulated genes that were not found in other studies. These genes are related to cell proliferation, movement and adhesion. They may be important for research into breast cancer mechanisms, particularly CST2 and CA4. A key signaling pathway, the ECM-receptor interaction signal pathway, was also identified as possibly involved in the development of breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s11658-019-0162-0) contains supplementary material, which is available to authorized users.

Stromal coexpression of uPA/PAI-1 protein predicts poor disease outcome in endocrine-treated postmenopausal patients with receptor-positive early breast cancer

BACKGROUND

To evaluate whether uPA/PAI-1 protein in hormone receptor-positive (HR+) breast tumor can predict prognosis in early breast cancer (BC).

METHODS

606 women with HR + BC who had ≥5 years of endocrine therapy and in whom tumor tissue was available were included in this analysis. Stromal uPA/PAI-1 protein expression was evaluated by immunohistochemistry and correlated with distant recurrence-free survival (DRFS) and overall survival (OS).

RESULTS

Stromal uPA was detected in 292/538 tumors (54.3%) while 269/505 samples (53.3%) exhibited stromal PAI-1. Co-expression of both proteins was found in 163/437 (37.3%) samples. Stromal uPA/PAI-1 co-expression was not associated with tumor size, age, nodal status, grading, or receptor status. Tumor stroma with both uPA and PAI-1 protein expression were more likely to have a shorter DRFS (HR: 1.87; 95%CI 1.18-2.96; p = 0.007) and OS (HR: 1.29; 95%CI 0.93-1.80; p = 0.129) than women without uPA/PAI-1 co-expression. After a median follow-up of 10 years, women with uPA/PAI-1-positive tumors experienced a significantly shorter DRFS (86.5% vs 72.4%; p < 0.001) and OS (70.4% vs 58.9%; p = 0.020) compared to women with uPA/PAI-1 negative tumors.

CONCLUSION

Stromal co-expression of uPA and PAI-1 in breast cancer predicts poor DRFS and OS in postmenopausal women with HR + early-stage BC who receive endocrine therapy.

Cancer-associated fibroblasts as key regulators of the breast cancer tumor microenvironment

Tumor cells exist in close proximity with non-malignant cells. Extensive and multilayered crosstalk between tumor cells and stromal cells tailors the tumor microenvironment (TME) to support survival, growth, and metastasis. Fibroblasts are one of the largest populations of non-malignant host cells that can be found within the TME of breast, pancreatic, and prostate tumors. Substantial scientific evidence has shown that these cancer-associated fibroblasts (CAFs) are not only associated with tumors by proximity but are also actively recruited to developing tumors where they can influence other cells of the TME as well as influencing tumor cell survival and metastasis. This review discusses the impact of CAFs on breast cancer biology and highlights their heterogeneity, origin and their role in tumor progression, ECM remodeling, therapy resistance, metastasis, and the challenges ahead of targeting CAFs to improve therapy response.

MiR-384 induces apoptosis and autophagy of non-small cell lung cancer cells through the negative regulation of Collagen α-1(X) chain gene

The present study aims to investigate the mechanism of miR-384 in non-small cell lung cancer (NSCLC) cell apoptosis and autophagy by regulating Collagen α-1(X) chain (COL10A1). Bioinformatics methods were applied to evaluate potential miRNAs and genes that might correlate with NSCLC. Tumor tissues and adjacent tissues from 104 NSCLC patients were collected and human NSCLC A549 cell line was selected for subsequent experiments. A549 cells were treated with miR-384 mimic, miR-384 inhibitor, or knockdown of COL10A1. Quantitative real-time PCR (qRT-PCR) and Western blotting were utilized to detect the levels of miR-384, COL10A, Survivin, Bcl-2, Bax, Bcl-xl, Beclin 1, and LC3 in tissues and cells. A series of biological assays including MTT assay, Annexin V-FITC/PI (propidium iodide) staining, immunofluorescence, monodansylcadaverine (MDC) staining were conducted to investigate the effects of miR-384 and COL10A1 on NSCLC cells. Tumorigenicity assay for nude rats was applied. Results obtained from the present study indicated that miR-384 down-regulated COL10A1 by targetting it. Compared with adjacent tissues, miR-384 expression was obviously reduced while COL10A1 expression was significantly enhanced in NSCLC tissues (all P<0.05). Outcomes in vivo and in vitro suggested that cell proliferation and tumorigenicity were inhibited while cell apoptosis and autophagy were induced in NSCLC cells treated with up-regulation of miR-384 or silence of COL10A1. In miR-384 inhibitor group, cell proliferation was improved, while cell apoptosis was reduced and cell autophagy was decreased whereas tumorigenicity of cells was strengthened. Based on the findings of our study, it was established that miR-384 could down-regulate COL10A1 levels, subsequently inhibiting cell proliferation and promoting cell apoptosis and autophagy in NSCLC cells.

ColXα1 is a stromal component that colocalizes with elastin in the breast tumor extracellular matrix

The tumor microenvironment regulates tissue development and homeostasis, and its dysregulation contributes to neoplastic progression. Increased expression of type X collagen α‐1 (ColXα1) in tumor‐associated stroma correlates with poor pathologic response to neoadjuvant chemotherapy in estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2)‐positive breast cancers. Evaluation of ColXα1 expression patterns suggests a potential connection with elastin fibers. To investigate the possible interaction between ColXα1 and elastin, we evaluated the expression of ColXα1 in relation to elastin fibers in normal breast tissue, ductal carcinoma in situ, and invasive breast carcinomas at cellular and subcellular levels. Our findings demonstrate that ColXα1 colocalizes with elastin in invasive breast cancer‐associated stroma by immunohistochemistry, immunofluorescence, and electron microscopy. In 212 invasive breast carcinomas, this complex was aberrantly and selectively expressed in tumor extracellular matrix in 79% of ER+/HER2−, 80% of ER+/HER2+, 76% of ER−/HER2+, and 58% of triple negative breast cancers. In contrast, ColXα1 was generally absent, while elastin was present perivascularly in normal breast tissue. ColXα1 and elastin were coexpressed in 58% of ductal carcinoma in situ (DCIS) in periductal areas. In mass‐forming DCIS with desmoplastic stroma, the complex was intensely expressed in periductal areas as well as within the tumor‐associated stroma in all cases. Our data suggest that the breast carcinoma neoplastic process may involve aberrant expression of ColXα1 and elastin in the tumor microenvironment emerging early at the DCIS stage. Enrichment of these complexes in tumor‐associated stroma may represent a stromal signature indicative of intrinsic differences between breast cancers. These findings shed light on investigation into the role of aberrant collagen complex expression in tumorigenesis and tumor progression which may be leveraged in therapeutic and theranostic applications.

High expression of COL10A1 is associated with poor prognosis in colorectal cancer

Background

High expression of collagen type X alpha 1 chain (COL10A1), a member of the collagen family, had been observed in various human cancers, but the detailed function and molecular mechanism of COL10A1 were largely unclear.

Aim

The aim of this study was to investigate the expression of COL10A1 in colorectal cancer (CRC) tissues and cells and to reveal its biological function and mechanism in CRC.

Materials and methods

Immunohistochemistry (IHC), real-time quantitative polymerase chain reaction (QPCR) and Western blot experiments were used to determine the clinical relevance between expression levels of COL10A1 and CRC.

Results

Compared with normal tissues, COL10A1 expression was significantly higher in CRC tissues. Biological functional experiments showed that overexpression of COL10A1 enhanced proliferation, migration, and invasion of CRC cells, and knockdown of COL10A1 inhibited tumorigenesis in vivo. Western blot assays showed that COL10A1 promoted the process of epithelial–mesenchymal transition (EMT). The overexpression of COL10A1 was associated with adverse prognosis in CRC by tissue microarray (TMA) analysis.

Conclusion

Our findings had provided evidences to support the fact that COL10A1 was abnormally up-expressed in CRC and involved in the progression of CRC and the process of EMT. Furthermore, we demonstrated that the high-level expression of COL10A1 was an independent risk factor of prognosis and overall survival in CRC patients. These suggested that COL10A1 might be a new potential target for cancer therapy in the future.

Protein biomarkers for subtyping breast cancer and implications for future research

INTRODUCTION

Breast cancer subtypes are currently defined by a combination of morphologic, genomic, and proteomic characteristics. These subtypes provide a molecular portrait of the tumor that aids diagnosis, prognosis, and treatment escalation/de-escalation options. Gene expression signatures describing intrinsic breast cancer subtypes for predicting risk of recurrence have been rapidly adopted in the clinic. Despite the use of subtype classifications, many patients develop drug resistance, breast cancer recurrence, or therapy failure. Areas covered: This review provides a summary of immunohistochemistry, reverse phase protein array, mass spectrometry, and integrative studies that are revealing differences in biological functions within and between breast cancer subtypes. We conclude with a discussion of rigor and reproducibility for proteomic-based biomarker discovery. Expert commentary: Innovations in proteomics, including implementation of assay guidelines and standards, are facilitating refinement of breast cancer subtypes. Proteomic and phosphoproteomic information distinguish biologically functional subtypes, are predictive of recurrence, and indicate likelihood of drug resistance. Actionable, activated signal transduction pathways can now be quantified and characterized. Proteomic biomarker validation in large, well-designed studies should become a public health priority to capitalize on the wealth of information gleaned from the proteome.

Stromal Clusterin Expression Predicts Therapeutic Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer

BACKGROUND

Expression of clusterin correlates with tumor progression and therapeutic response in several human malignancies, including breast cancer. However, its predictive value in the neoadjuvant setting in breast cancer remains unexplored. The objective of this explorative study was to determine whether clusterin expression in breast cancer correlated with clinical pathologic characteristics and whether its expression was predictive of response to neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

We determined the clusterin expression pattern in 72 triple negative breast cancers (TNBC) treated with NAC before surgery. Clusterin expression was evaluated by immunohistochemistry and was correlated with pathologic characteristics and response to NAC using residual cancer burden score.

RESULTS

Immunohistochemistry analysis revealed a differential pattern of expression between tumor and stroma. Clusterin expression in the tumor associated stroma as opposed to expression by the neoplastic epithelium was significantly associated with neoadjuvant-treated TNBC. Low stromal clusterin, low stromal content, and high tumor-infiltrating lymphocytes were associated with a significantly greater likelihood of achieving a good pathologic response as reflected by lower residual cancer burden scores (P = .002, P = .003, and P = .001, respectively). Tumor and/or stromal clusterin expression were not associated with patient age, tumor histologic grade, stage, and lymph node status.

CONCULSION

This study suggests a potential role for the assessment of stromal clusterin as a predictive biomarker for response of TNBC to neoadjuvant therapy. Further validation of this biomarker in a large study is needed.

Molecular characterization of breast cancer CTCs associated with brain metastasis

The enumeration of EpCAM-positive circulating tumor cells (CTCs) has allowed estimation of overall metastatic burden in breast cancer patients. However, a thorough understanding of CTCs associated with breast cancer brain metastasis (BCBM) is necessary for early identification and evaluation of treatment response to BCBM. Here we report that BCBM CTCs is enriched in a distinct sub-population of cells identifiable by their biomarker expression and mutational content. Deriving from a comprehensive analysis of CTC transcriptomes, we discovered a unique "circulating tumor cell gene signature" that is distinct from primary breast cancer tissues. Further dissection of the circulating tumor cell gene signature identified signaling pathways associated with BCBM CTCs that may have roles in potentiating BCBM. This study proposes CTC biomarkers and signaling pathways implicated in BCBM that may be used either as a screening tool for brain micro-metastasis detection or for making rational treatment decisions and monitoring therapeutic response in patients with BCBM.Characterization of CTCs derived from breast cancer patients with brain metastasis (BCBM) may allow for early diagnosis of brain metastasis and/or help for treatment choice and its efficacy. In this study, the authors identify a unique signature, based on patient-derived CTCs transcriptomes, for BCBM- CTCs that is different from primary tumors.

Risk score based on three mRNA expression predicts the survival of bladder cancer

Bladder cancer (BLCA) is one of the most malignant cancers worldwide, and its prognosis varies. 1214 BLCA samples in five different datasets and 2 platforms were enrolled in this study. By utilizing the gene expression in The Cancer Genome Atlas (TCGA) dataset, and another two datasets, in GSE13507 and GSE31684, we constructed a risk score staging system with Cox multivariate regression to evaluate predict the outcome of BLCA patients. Three genes consist of RCOR1, ST3GAL5, and COL10A1 were used to predict the survival of BLCA patients. The patients with low risk score have a better survival rate than those with high risk score, significantly. The survival profiles of another two datasets (GSE13507 and GSE31684), which were used for candidate gene selection, were similar as the training dataset (TCGA). Furthermore, survival prediction effect of risk score staging system in another 2 independent datasets, GSE40875 and E-TABM-4321, were also validated. Compared with other clinical observations, and the risk score performs better in evaluating the survival of BLCA patients. Moreover, the correlation between radiation were also evaluated, and we found that patients have a poor survival in high risk group, regardless of radiation. Gene Set Enrichment Analysis was also implemented to find the difference between high-risk and low-risk groups on biological pathways, and focal adhesion and JAK signaling pathway were significantly enriched. In summary, we developed a risk staging model for BLCA patients with three gene expression. The model is independent from and performs better than other clinical information.

Collagen type III α1 as a useful diagnostic immunohistochemical marker for fibroepithelial lesions of the breast

Phyllodes tumors (PTs) of the breast constitute an uncommon group of fibroepithelial neoplasms that are classified into benign, borderline, and malignant categories based on a constellation of histologic characteristics including cytologic atypia, mitotic count, degree of stromal cellularity, stromal overgrowth, and microscopic margins. Accurately and reproducibly differentiating these tumors is a long-standing diagnostic challenge. In addition, the distinction between benign PT from cellular fibroadenoma (FA) is especially difficult because of overlapping microscopic features. We have previously shown differential expression of various collagens, including collagen type III α1 (Col3A) in breast carcinomas. In this study, we evaluated clinicopathological characteristics of 95 cases of fibroepithelial lesions including 56 PTs and 39 FAs (25 cellular FA, 14 typical FA) and correlated them with the immunohistochemical staining pattern for Col3A. We found that stromal Col3A expression was significantly increased in PTs when compared with FAs (P < .0001). Among the PT groups, there was significantly increased expression from benign tumors through borderline to malignant tumors. High Col3A expression was associated with PT type, irregular margin status, and high mitotic activity. A distinct periductal cuffing pattern of Col3A staining was unique to PTs and absent in FAs. These findings suggest that Col3A can be a potential adjunct marker for both differentiating FA from PT and assessing malignant potential in PTs.