COL11A1 promotes tumor progression and predicts poor clinical outcome in ovarian cancer

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.

Expression and function of NF-Y subunits in cancer

NF-Y is a Transcription Factor (TF) targeting the CCAAT box regulatory element. It consists of the NF-YB/NF-YC heterodimer, each containing an Histone Fold Domain (HFD), and the sequence-specific subunit NF-YA. NF-YA expression is associated with cell proliferation and absent in some post-mitotic cells. The review summarizes recent findings impacting on cancer development. The logic of the NF-Y regulome points to pro-growth, oncogenic genes in the cell-cycle, metabolism and transcriptional regulation routes. NF-YA is involved in growth/differentiation decisions upon cell-cycle re-entry after mitosis and it is widely overexpressed in tumors, the HFD subunits in some tumor types or subtypes. Overexpression of NF-Y -mostly NF-YA- is oncogenic and decreases sensitivity to anti-neoplastic drugs. The specific roles of NF-YA and NF-YC isoforms generated by alternative splicing -AS- are discussed, including the prognostic value of their levels, although the specific molecular mechanisms of activity are still to be deciphered.

Association of genetic variation in COL11A1 with adolescent idiopathic scoliosis

Adolescent idiopathic scoliosis (AIS) is a common and progressive spinal deformity in children that exhibits striking sexual dimorphism, with girls at more than fivefold greater risk of severe disease compared to boys. Despite its medical impact, the molecular mechanisms that drive AIS are largely unknown. We previously defined a female-specific AIS genetic risk locus in an enhancer near the PAX1 gene. Here, we sought to define the roles of PAX1 and newly identified AIS-associated genes in the developmental mechanism of AIS. In a genetic study of 10,519 individuals with AIS and 93,238 unaffected controls, significant association was identified with a variant in COL11A1 encoding collagen (α1) XI (rs3753841; NM_080629.2_c.4004C>T; p.(Pro1335Leu); p=7.07E-11, OR = 1.118). Using CRISPR mutagenesis we generated Pax1 knockout mice (Pax1-/-). In postnatal spines we found that PAX1 and collagen (α1) XI protein both localize within the intervertebral disc-vertebral junction region encompassing the growth plate, with less collagen (α1) XI detected in Pax1-/- spines compared to wild-type. By genetic targeting we found that wild-type Col11a1 expression in costal chondrocytes suppresses expression of Pax1 and of Mmp3, encoding the matrix metalloproteinase 3 enzyme implicated in matrix remodeling. However, the latter suppression was abrogated in the presence of the AIS-associated COL11A1P1335L mutant. Further, we found that either knockdown of the estrogen receptor gene Esr2 or tamoxifen treatment significantly altered Col11a1 and Mmp3 expression in chondrocytes. We propose a new molecular model of AIS pathogenesis wherein genetic variation and estrogen signaling increase disease susceptibility by altering a PAX1-COL11a1-MMP3 signaling axis in spinal chondrocytes.

Limitations and potential of immunotherapy in ovarian cancer

Ovarian cancer (OC) is the third most common gynecological cancer and alone has an emergence rate of approximately 308,069 cases worldwide (2020) with dire survival rates. To put it into perspective, the mortality rate of OC is three times higher than that of breast cancer and it is predicted to only increase significantly by 2040. The primary reasons for such a high rate are that the physical symptoms of OC are detectable only during the advanced phase of the disease when resistance to chemotherapies is high and around 80% of the patients that do indeed respond to chemotherapy initially, show a poor prognosis subsequently. This highlights a pressing need to develop new and effective therapies to tackle advanced OC to improve prognosis and patient survival. A major advance in this direction is the emergence of combination immunotherapeutic methods to boost CD8+ T cell function to tackle OC. In this perspective, we discuss our view of the current state of some of the combination immunotherapies in the treatment of advanced OC, their limitations, and potential approaches toward a safer and more effective response.

Association of genetic variation in COL11A1 with adolescent idiopathic scoliosis

Adolescent idiopathic scoliosis (AIS) is a common and progressive spinal deformity in children that exhibits striking sexual dimorphism, with girls at more than five-fold greater risk of severe disease compared to boys. Despite its medical impact, the molecular mechanisms that drive AIS are largely unknown. We previously defined a female-specific AIS genetic risk locus in an enhancer near the PAX1 gene. Here we sought to define the roles of PAX1 and newly-identified AIS-associated genes in the developmental mechanism of AIS. In a genetic study of 10,519 individuals with AIS and 93,238 unaffected controls, significant association was identified with a variant in COL11A1 encoding collagen (α1) XI (rs3753841; NM_080629.2_c.4004C>T; p.(Pro1335Leu); P=7.07e-11, OR=1.118). Using CRISPR mutagenesis we generated Pax1 knockout mice (Pax1-/-). In postnatal spines we found that PAX1 and collagen (α1) XI protein both localize within the intervertebral disc (IVD)-vertebral junction region encompassing the growth plate, with less collagen (α1) XI detected in Pax1-/- spines compared to wildtype. By genetic targeting we found that wildtype Col11a1 expression in costal chondrocytes suppresses expression of Pax1 and of Mmp3, encoding the matrix metalloproteinase 3 enzyme implicated in matrix remodeling. However, this suppression was abrogated in the presence of the AIS-associated COL11A1P1335L mutant. Further, we found that either knockdown of the estrogen receptor gene Esr2, or tamoxifen treatment, significantly altered Col11a1 and Mmp3 expression in chondrocytes. We propose a new molecular model of AIS pathogenesis wherein genetic variation and estrogen signaling increase disease susceptibility by altering a Pax1-Col11a1-Mmp3 signaling axis in spinal chondrocytes.

Usefulness of COL11A1 as a Prognostic Marker of Tumor Infiltration

BACKGROUND

Determining the infiltration of carcinomas is essential for the proper follow-up and treatment of cancer patients. However, it continues to be a diagnostic challenge for pathologists in multiple types of tumors. In previous studies (carried out in surgical specimens), the protein COL11A1 has been postulated as an infiltration marker mainly expressed in the extracellular matrix (ECM). We hypothesized that a differential expression of COL11A1 may exist in the peritumoral stroma of tumors that have acquired infiltrating properties and that it may be detected in the small biopsies usually available in normal clinical practice.

MATERIAL AND METHODS

In our study, we performed immunohistochemical staining in more than 350 invasive and noninvasive small samples obtained via core needle biopsy (CNB), colonoscopy, or transurethral resection of bladder tumor (TURBT) of breast, colorectal, bladder, and ovarian cancer.

RESULTS

Our results revealed that COL11A1 immunostaining had a sensitivity to classify the samples into infiltrative vs. noninfiltrative tumors of 94% (breast), 97% (colorectal), >90% (bladder), and 74% (ovarian); and a specificity of 97% (breast), 100% (colorectal), and >90% (bladder). In ovarian cancer, the negative predictive value (0.59) did not present improvement over the usual histopathological markers. In all samples tested, the cumulative sensitivity was 86% and the specificity 96% (p < 0.0001).

CONCLUSIONS

COL11A1-positive immunostaining in small biopsies of breast, colon, bladder and ovarian cancer is an accurate predictive marker of tumor infiltration that can be easily implemented in daily clinical practice.

Therapeutic Targets of Monoclonal Antibodies Used in the Treatment of Cancer: Current and Emerging

Cancer is one of the leading global causes of death and disease, and treatment options are constantly evolving. In this sense, the use of monoclonal antibodies (mAbs) in immunotherapy has been considered a fundamental aspect of modern cancer therapy. In order to avoid collateral damage, it is indispensable to identify specific molecular targets or biomarkers of therapy and/or diagnosis (theragnostic) when designing an appropriate immunotherapeutic regimen for any type of cancer. Furthermore, it is important to understand the currently employed mAbs in immunotherapy and their mechanisms of action in combating cancer. To achieve this, a comprehensive understanding of the biology of cancer cell antigens, domains, and functions is necessary, including both those presently utilized and those emerging as potential targets for the design of new mAbs in cancer treatment. This review aims to provide a description of the therapeutic targets utilized in cancer immunotherapy over the past 5 years, as well as emerging targets that hold promise as potential therapeutic options in the application of mAbs for immunotherapy. Additionally, the review explores the mechanisms of actin of the currently employed mAbs in immunotherapy.

The downregulation of miR-509-3p expression by collagen type XI alpha 1-regulated hypermethylation facilitates cancer progression and chemoresistance via the DNA methyltransferase 1/Small ubiquitin-like modifier-3 axis in ovarian cancer cells

BACKGROUND

MicroRNAs are a group of small non-coding RNAs that are involved in development and diseases such as cancer. Previously, we demonstrated that miR-335 is crucial for preventing collagen type XI alpha 1 (COL11A1)-mediated epithelial ovarian cancer (EOC) progression and chemoresistance. Here, we examined the role of miR-509-3p in EOC.

METHODS

The patients with EOC who underwent primary cytoreductive surgery and postoperative platinum-based chemotherapy were recruited. Their clinic-pathologic characteristics were collected, and disease-related survivals were determined. The COL11A1 and miR-509-3p mRNA expression levels of 161 ovarian tumors were determined by real-time reverse transcription-polymerase chain reaction. Additionally, miR-509-3p hypermethylation was evaluated by sequencing in these tumors. The A2780CP70 and OVCAR-8 cells transfected with miR-509-3p mimic, while the A2780 and OVCAR-3 cells transfected with miR-509-3p inhibitor. The A2780CP70 cells transfected with a small interference RNA of COL11A1, and the A2780 cells transfected with a COL11A1 expression plasmid. Site-directed mutagenesis, luciferase, and chromatin immunoprecipitation assays were performed in this study.

RESULTS

Low miR-509-3p levels were correlated with disease progression, a poor survival, and high COL11A1 expression levels. In vivo studies reinforced these findings and indicated that the occurrence of invasive EOC cell phenotypes and resistance to cisplatin are decreased by miR-509-3p. The miR-509-3p promoter region (p278) is important for miR-509-3p transcription regulation via methylation. The miR-509-3p hypermethylation frequency was significantly higher in EOC tumors with a low miR-509-3p expression than in those with a high miR-509-3p expression. The patients with miR-509-3p hypermethylation had a significantly shorter overall survival (OS) than those without miR-509-3p hypermethylation. Mechanistic studies further indicated that miR-509-3p transcription was downregulated by COL11A1 through a DNA methyltransferase 1 (DNMT1) stability increase. Moreover, miR-509-3p targets small ubiquitin-like modifier (SUMO)-3 to regulate EOC cell growth, invasiveness, and chemosensitivity.

CONCLUSION

The miR-509-3p/DNMT1/SUMO-3 axis may be an ovarian cancer treatment target.

Single-Cell RNA Sequencing: Technological Progress and Biomedical Application in Cancer Research

Single-cell RNA-seq (scRNA-seq) is a revolutionary technology that allows for the genomic investigation of individual cells in a population, allowing for the discovery of unusual cells associated with cancer and metastasis. ScRNA-seq has been used to discover different types of cancers with poor prognosis and medication resistance such as lung cancer, breast cancer, ovarian cancer, and gastric cancer. Besides, scRNA-seq is a promising method that helps us comprehend the biological features and dynamics of cell development, as well as other disorders. This review gives a concise summary of current scRNA-seq technology. We also explain the main technological steps involved in implementing the technology. We highlight the present applications of scRNA-seq in cancer research, including tumor heterogeneity analysis in lung cancer, breast cancer, and ovarian cancer. In addition, this review elucidates potential applications of scRNA-seq in lineage tracing, personalized medicine, illness prediction, and disease diagnosis, which reveals that scRNA-seq facilitates these events by producing genetic variations on the single-cell level.

Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods

Breast cancer is one of the most prevalent types of cancer diagnosed globally and continues to have a significant impact on the global number of cancer deaths. Despite all efforts of epidemiological and experimental research, therapeutic concepts in cancer are still unsatisfactory. Gene expression datasets are widely used to discover the new biomarkers and molecular therapeutic targets in diseases. In the present study, we analyzed four datasets using R packages with accession number GSE29044, GSE42568, GSE89116, and GSE109169 retrieved from NCBI-GEO and differential expressed genes (DEGs) were identified. Protein-protein interaction (PPI) network was constructed to screen the key genes. Subsequently, the GO function and KEGG pathways were analyzed to determine the biological function of key genes. Expression profile of key genes was validated in MCF-7 and MDA-MB-231 human breast cancer cell lines using qRT-PCR. Overall expression level and stage wise expression pattern of key genes was determined by GEPIA. The bc-GenExMiner was used to compare expression level of genes among groups of patients with respect to age factor. OncoLnc was used to analyze the effect of expression levels of LAMA2, TIMP4, and TMTC1 on the survival of breast cancer patients. We identified nine key genes, of which COL11A1, MMP11, and COL10A1 were found up-regulated and PCOLCE2, LAMA2, TMTC1, ADAMTS5, TIMP4, and RSPO3 were found down-regulated. Similar expression pattern of seven among nine genes (except ADAMTS5 and RSPO3) was observed in MCF-7 and MDA-MB-231 cells. Further, we found that LAMA2, TMTC1, and TIMP4 were significantly expressed among different age groups of patients. LAMA2 and TIMP4 were found significantly associated and TMTC1 was found less correlated with breast cancer occurrence. We found that the expression level of LAMA2, TIMP4, and TMTC1 was abnormal in all TCGA tumors and significantly associated with poor survival.

Circular RNAs as the pivotal regulators of epithelial-mesenchymal transition in gastrointestinal tumor cells

Gastrointestinal (GI) cancers, as the most common human malignancies are always considered one of the most important health challenges in the world. Late diagnosis in advanced tumor stages is one of the main reasons for the high mortality rate and treatment failure in these patients. Therefore, investigating the molecular pathways involved in GI tumor progression is required to introduce the efficient markers for the early tumor diagnosis. Epithelial-mesenchymal transition (EMT) is one of the main cellular mechanisms involved in the GI tumor metastasis. Non-coding RNAs (ncRNAs) are one of the main regulatory factors in EMT process. Circular RNAs (circRNAs) are a group of covalently closed loop ncRNAs that have higher stability in body fluids compared with other ncRNAs. Considering the importance of circRNAs in regulation of EMT process, in the present review we discussed the role of circRNAs in EMT process during GI tumor invasion. It has been reported that circRNAs mainly affect the EMT process through the regulation of EMT-specific transcription factors and signaling pathways such as WNT, PI3K/AKT, TGF-β, and MAPK. This review can be an effective step in introducing a circRNA/EMT based diagnostic panel marker for the early tumor detection among GI cancer patients.

A mutational signature and significantly mutated driver genes associated with immune checkpoint inhibitor response across multiple cancers

Immune checkpoint inhibitor (ICI) treatments dramatically prolong the survival outcomes of several advanced cancers. However, as multiple studies reported, only a subset of patients could benefit from the ICI treatment. In this study, we aim to uncover novel molecular biomarkers predictive of immunotherapy efficacy across multiple cancers. Pre-treatment somatic mutational profiles and immunotherapy clinical information were obtained from 1097 samples of multiple cancers, including melanoma, non-small cell lung cancer (NSCLC), clear cell renal cell carcinoma (ccRCC), bladder carcinoma (BLCA), and head and neck squamous cell carcinoma (HNSCC). Mutational signatures, molecular subtypes, and significantly mutated genes (SMGs) were determined, and their connections with ICI response and outcome were also evaluated. We extracted a total of six mutational signatures across all samples. Among, a mutational signature featured by T > C substitutions was identified to associate with an ICI resistance. A molecular subtype determined based on mutational activities was connected with a significantly improved ICI response rate and outcome. Totaling 50 SMGs were identified, and we observed that patients with COL11A1 or COL4A6 mutations exhibited a superior ICI treatment efficacy than those without such mutations. In this study, we uncovered several novel molecular determinants of cancer immunotherapy response under a multiple-cancer setting, which provides clues for enrolling patients to receive immunotherapy and customizing personalized treatment strategies.

The Downregulation of miR-509-3p Expression by Collagen Type XI Alpha 1-Regulated Hypermethylation Facilitates Cancer Progression and Chemoresistance via the DNA Methyltransferase 1/Small Ubiquitin-like Modifier-3 Axis in Ovarian Cancer Cells

Background MicroRNAs are a group of small non-coding RNAs that are involved in development and diseases such as cancer. Previously, we demonstrated that miR-335 is crucial for preventing collagen type XI alpha 1 (COL11A1)-mediated epithelial ovarian cancer (EOC) progression and chemoresistance. Here, we examined the role of miR-509-3p in EOC. Methods The patients with EOC who underwent primary cytoreductive surgery and postoperative platinum-based chemotherapy were recruited. Their clinic-pathologic characteristics were collected, and disease-related survivals were determined. The COL11A1 and miR-509-3p mRNA expression levels of 161 ovarian tumors were determined by real-time reverse transcription-polymerase chain reaction. Additionally, miR-509-3p hypermethylation was evaluated by sequencing in these tumors. The A2780CP70 and OVCAR-8 cells transfected with miR-509-3p mimic, while the A2780 and OVCAR-3 cells transfected with miR-509-3p inhibitor. The A2780CP70 cells transfected with a small interference RNA of COL11A1, and the A2780 cells transfected with a COL11A1 expression plasmid. Site-directed mutagenesis, luciferase, and chromatin immunoprecipitation assays were performed in this study. Results Low miR-509-3p levels were correlated with disease progression, a poor survival, and high COL11A1 expression levels. In vivo studies reinforced these findings and indicated that the occurrence of invasive EOC cell phenotypes and resistance to cisplatin are decreased by miR-509-3p. The miR-509-3p promoter region (p278) is important for miR-509-3p transcription regulation via methylation. The miR-509-3p hypermethylation frequency was significantly higher in EOC tumors with a low miR-509-3p expression than in those with a high miR-509-3p expression. The patients with miR-509-3p hypermethylation had a significantly shorter overall survival (OS) than those without miR-509-3p hypermethylation. Mechanistic studies further indicated that miR-509-3p transcription was downregulated by COL11A1 through a DNA methyltransferase 1 (DNMT1) phosphorylation and stability increase. Moreover, miR-509-3p targets small ubiquitin-like modifier (SUMO)-3 to regulate EOC cell growth, invasiveness, and chemosensitivity. Conclusion The miR-509-3p/DNMT1/SUMO-3 axis may be an ovarian cancer treatment target.

Identification of prognostic cancer-associated fibroblast markers in luminal breast cancer using weighted gene co-expression network analysis

Background

Cancer-associated fibroblasts (CAFs) play a pivotal role in cancer progression and are known to mediate endocrine and chemotherapy resistance through paracrine signaling. Additionally, they directly influence the expression and growth dependence of ER in Luminal breast cancer (LBC). This study aims to investigate stromal CAF-related factors and develop a CAF-related classifier to predict the prognosis and therapeutic outcomes in LBC.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to obtain mRNA expression and clinical information from 694 and 101 LBC samples, respectively. CAF infiltrations were determined by estimating the proportion of immune and cancer cells (EPIC) method, while stromal scores were calculated using the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm. Weighted gene co-expression network analysis (WGCNA) was used to identify stromal CAF-related genes. A CAF risk signature was developed through univariate and least absolute shrinkage and selection operator method (LASSO) Cox regression model. The Spearman test was used to evaluate the correlation between CAF risk score, CAF markers, and CAF infiltrations estimated through EPIC, xCell, microenvironment cell populations-counter (MCP-counter), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. The TIDE algorithm was further utilized to assess the response to immunotherapy. Additionally, Gene set enrichment analysis (GSEA) was applied to elucidate the molecular mechanisms underlying the findings.

Results

We constructed a 5-gene prognostic model consisting of RIN2, THBS1, IL1R1, RAB31, and COL11A1 for CAF. Using the median CAF risk score as the cutoff, we classified LBC patients into high- and low-CAF-risk groups and found that those in the high-risk group had a significantly worse prognosis. Spearman correlation analyses demonstrated a strong positive correlation between the CAF risk score and stromal and CAF infiltrations, with the five model genes showing positive correlations with CAF markers. In addition, the TIDE analysis revealed that high-CAF-risk patients were less likely to respond to immunotherapy. Gene set enrichment analysis (GSEA) identified significant enrichment of ECM receptor interaction, regulation of actin cytoskeleton, epithelial-mesenchymal transition (EMT), and TGF-β signaling pathway gene sets in the high-CAF-risk group patients.

Conclusion

The five-gene prognostic CAF signature presented in this study was not only reliable for predicting prognosis in LBC patients, but it was also effective in estimating clinical immunotherapy response. These findings have significant clinical implications, as the signature may guide tailored anti-CAF therapy in combination with immunotherapy for LBC patients.

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.

MPZL1 upregulation promotes tumor metastasis and correlates with unfavorable prognosis in non-small cell lung cancer

Non-small cell lung cancer (NSCLC), accounting for 85% of all lung cancer, is one of the leading causes of cancer-related death worldwide. Previously, we demonstrated that MPZL1 gene amplification promotes liver cancer metastasis through activating Src/Cortactin pathway. However, the clinical relevance and biological roles of the MPZL1 gene in lung cancer are still unknown. Here, we found that MPZL1 expression upregulates in human NSCLC, which is partly due to the copy number amplification of this gene. Next, we observed that high MPZL1 expression correlates with unfavorable prognosis of NSCLC patients. We further demonstrated that ectopic MPZL1 overexpression promotes in vitro migratory but not proliferation and colony formation abilities of both H1299 and H460 cells. Consistently, we found that MPZL1 knockdown impairs the migratory abilities of A549 and H1775 cells. Moreover, we found that MPZL1 knockdown inhibits in vivo metastatic but not tumor growth abilities of the A549 cells. Additionally, a total of 297 differentially expressed genes (DEGs) were identified by RNA sequencing in A549 cells upon MPZL1 knockdown. By integrative analysis of DEGs regulated by MPZL1 in A549 cells and human NSCLC tissues, we revealed that COL11A1 is the potential effector gene that positively regulated by MPZL1 and correlates with poor prognosis of NSCLC patients. In conclusion, our work indicates that one of the mechanisms by which MPZL1 promotes NSCLC metastasis is through upregulating the COL11A1, and MPZL1 can be used as a biomarker to predict the prognosis of NSCLC patients.

Extracellular matrix profiles determine risk and prognosis of the squamous cell carcinoma subtype of non-small cell lung carcinoma

BACKGROUND

Squamous cell carcinoma (SqCC) is a subtype of non-small cell lung cancer for which patient prognosis remains poor. The extracellular matrix (ECM) is critical in regulating cell behavior; however, its importance in tumor aggressiveness remains to be comprehensively characterized.

METHODS

Multi-omics data of SqCC human tumor specimens was combined to characterize ECM features associated with initiation and recurrence. Penalized logistic regression was used to define a matrix risk signature for SqCC tumors and its performance across a panel of tumor types and in SqCC premalignant lesions was evaluated. Consensus clustering was used to define prognostic matreotypes for SqCC tumors. Matreotype-specific tumor biology was defined by integration of bulk RNAseq with scRNAseq data, cell type deconvolution, analysis of ligand-receptor interactions and enriched biological pathways, and through cross comparison of matreotype expression profiles with aging and idiopathic pulmonary fibrosis lung profiles.

RESULTS

This analysis revealed subtype-specific ECM signatures associated with tumor initiation that were predictive of premalignant progression. We identified an ECM-enriched tumor subtype associated with the poorest prognosis. In silico analysis indicates that matrix remodeling programs differentially activate intracellular signaling in tumor and stromal cells to reinforce matrix remodeling associated with resistance and progression. The matrix subtype with the poorest prognosis resembles ECM remodeling in idiopathic pulmonary fibrosis and may represent a field of cancerization associated with elevated cancer risk.

CONCLUSIONS

Collectively, this analysis defines matrix-driven features of poor prognosis to inform precision medicine prevention and treatment strategies towards improving SqCC patient outcome.

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.

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.

Potential biomarkers and immune characteristics of small bowel adenocarcinoma

Small bowel adenocarcinoma (SBA) is a gastrointestinal malignancy with low incidence but poor prognosis, and its pathogenesis is still unclear. This study aimed to explore potential disease-causing biomarkers of SBA. The gene expression datasets of SBA and normal samples were downloaded from the Gene Expression Omnibus database. First, differential gene expression analysis and weighted gene coexpression network analysis (WGCNA) were performed. Common genes (CGs) were obtained by intersection of differentially expressed genes (DEGs) and optimal modal genes of WGCNA. Subsequently, a protein‒protein interaction network was established to screen hub genes, and target genes were obtained by Lasso regression analysis of hub genes. An SBA risk prediction model was established based on target genes. The prediction accuracy of the model was evaluated by the area under the receiver operating characteristic curve (AUC). The levels of immune cell infiltration and activation of immune pathways were compared between SBA and normal samples using the "ggpubr" and "reshape2" packages. A total of 1058 DEGs were identified. WGCNA showed that the signature gene in the brown module was significantly associated with SBA (p = 7E−17), and 469 CGs were obtained. Four target genes (APOA4, APOB, COL1A2, FN1) were identified and showed excellent prediction of SBA risk (AUC = 0.965). In addition, active dendritic cells and macrophages showed higher infiltration levels in SBA. Meanwhile, the APC_co_stimulation pathway and parainflammation pathway were strongly active in SBA. Four target genes (APOA4, APOB, COL1A2, FN1) may be involved in the pathogenesis of small bowel adenocarcinoma.

Survival Analysis with High-Dimensional Omics Data Using a Threshold Gradient Descent Regularization-Based Neural Network Approach

Analysis of data with a censored survival response and high-dimensional omics measurements is now common. Most of the existing analyses are based on specific (semi)parametric models, in particular the Cox model. Such analyses may be limited by not having sufficient flexibility, for example, in accommodating nonlinearity. For categorical and continuous responses, neural networks (NNs) have provided a highly competitive alternative. Comparatively, NNs for censored survival data remain limited. Omics measurements are usually high-dimensional, and only a small subset is expected to be survival-associated. As such, regularized estimation and selection are needed. In the existing NN studies, this is usually achieved via penalization. In this article, we propose adopting the threshold gradient descent regularization (TGDR) technique, which has competitive performance (for example, when compared to penalization) and unique advantages in regression analysis, but has not been adopted with NNs. The TGDR-based NN has a highly sensible formulation and an architecture different from the unregularized and penalization-based ones. Simulations show its satisfactory performance. Its practical effectiveness is further established via the analysis of two cancer omics datasets. Overall, this study can provide a practical and useful new way in the NN paradigm for survival analysis with high-dimensional omics measurements.

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.

Interplay Between Immune and Cancer-Associated Fibroblasts: A Path to Target Metalloproteinases in Penile Cancer

Extracellular matrix (ECM) remodeling and inflammation have been reported in penile carcinomas (PeCa). However, the cell types and cellular crosstalk involved in PeCa are unexplored. We aimed to characterize the complexity of cells and pathways involved in the tumor microenvironment (TME) in PeCa and propose target molecules associated with the TME. We first investigated the prognostic impact of cell types with a secretory profile to identify drug targets that modulate TME-enriched cells. The secretome analysis using the PeCa transcriptome revealed the enrichment of inflammation and extracellular matrix pathways. Twenty-three secreted factors were upregulated, mainly collagens and matrix metalloproteinases (MMPs). The deregulation of collagens and MMPs was confirmed by Quantitative reverse transcription - polymerase chain reaction (RT-qPCR). Further, the deconvolution method (digital cytometry) of the bulk samples revealed a high proportion of macrophages and dendritic cells (DCs) and B cells. Increased DCs and B cells were associated with better survival. A high proportion of cancer-associated fibroblasts (CAFs) was observed in low-survival patients. Patients with increased CAFs had decreased immune cell proportions. The treatment with the MMP inhibitor GM6001 in CAF cells derived from PeCa resulted in altered cell viability. We reported a crosstalk between immune cells and CAFs, and the proportion of these cell populations was associated with prognosis. We demonstrate that a drug targeting MMPs modulates CAFs, expanding the therapeutic options of PeCa.

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.

Identification of COL1A1 associated with immune infiltration in brain lower grade glioma

Brain low grade gliomas (LGG) often give serious clinical symptoms due to the invasion towards nervous system, affecting the life quality of patients. Collagen type I alpha 1(COL1A1) is the main component of type I collagen. Although there are many reports about abnormal expression of COL1A1 in various tumors, specific role and clinical significance of COL1A1 in LGG have not yet been elucidated. In this work, Tumor Immune Estimation Resource database was used for detecting the expression level of COL1A1 in cancer and normal tissues, and aimed to explore the relationship between COL1A1 and tumor immune infiltration. We applied Kaplan-Meier to analyze the role of COL1A1 in clinical prognosis. Univariate survival rate and multivariate Cox analysis were used to compare clinical characteristics and survival rate. The relativity between the expression of COL1A1 and the tumor microenvironment was evaluated using ESTIMATE algorithm. Finally, the relationship between expression level of COL1A1 and gene marker sets of immune cell infiltration was investigated via TIMER. According to TCGA, COL1A1 overexpression was correlated with overall survival (OS), progression free interval (PFI) and disease specific survival (DSS) of multiple tumors, especially in LGG. Multivariate analysis showed that COL1A1 expression was an independent prognostic factor for LGG. The expression of COL1A1 was positively correlated with the infiltration of CD4 + T and CD8 + T cells, neutrophils, macrophages and dendritic cells in LGG. In addition, there was a strong correlation between expression of COL1A1 and different immune marker sets in LGG. The results suggest that COL1A1 is related with tumor immune infiltration of LGG.

COL5A1 Promotes the Progression of Gastric Cancer by Acting as a ceRNA of miR-137-3p to Upregulate FSTL1 Expression

MicroRNAs (miRNAs) and their target genes have been shown to play an important role in gastric cancer but have not been fully clarified. Therefore, our goal was to identify the key miRNA-mRNA regulatory network in gastric cancer by utilizing a variety of bioinformatics analyses and experiments. A total of 242 miRNAs and 1080 genes were screened from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. Then, survival-related differentially expressed miRNAs and their differentially expressed target genes were screened. Twenty hub genes were identified from their protein-protein interaction network. After weighted gene co-expression network analysis was conducted, we selected miR-137-3p and its target gene, COL5A1, for further research. We found that miR-137-3p was significantly downregulated and that overexpression of miR-137-3p suppressed the proliferation, invasion, and migration of gastric cancer cells. Furthermore, we found that its target gene, COL5A1, could regulate the expression of another hub gene, FSTL1, by sponging miR-137-3p, which was confirmed by dual-luciferase reporter assays. Knockdown of COL5A1 inhibited the proliferation, invasion, and migration of gastric cancer cells, which could be rescued by the miR-137-3p inhibitor or overexpression of FSTL1. Ultimately, bioinformatics analyses showed that the expression of FSTL1 was highly correlated with immune infiltration.

Identification of a Recurrence Gene Signature for Ovarian Cancer Prognosis by Integrating Single-Cell RNA Sequencing and Bulk Expression Datasets

Ovarian cancer is one of the most common gynecological malignancies in women, with a poor prognosis and high mortality. With the expansion of single-cell RNA sequencing technologies, the inner biological mechanism involved in tumor recurrence should be explored at the single-cell level, and novel prognostic signatures derived from recurrence events were urgently identified. In this study, we identified recurrence-related genes for ovarian cancer by integrating two Gene Expression Omnibus datasets, including an ovarian cancer single-cell RNA sequencing dataset (GSE146026) and a bulk expression dataset (GSE44104). Based on these recurrence genes, we further utilized the merged expression dataset containing a total of 524 ovarian cancer samples to identify prognostic signatures and constructed a 13-gene risk model, named RMGS (recurrence marker gene signature). Based on the RMGS score, the samples were stratified into high-risk and low-risk groups, and these two groups displayed significant survival difference in two independent validation cohorts including The Cancer Genome Atlas (TCGA). Also, the RMGS score remained significantly independent in multivariate analysis after adjusting for clinical factors, including the tumor grade and stage. Furthermore, there existed close associations between the RMGS score and immune characterizations, including checkpoint inhibition, EMT signature, and T-cell infiltration. Finally, the associations between RMGS scores and molecular subtypes revealed that samples with mesenchymal subtypes displayed higher RMGS scores. In the meanwhile, the genomics characterization from these two risk groups was also identified. In conclusion, the recurrence-related RMGS model we identified could provide a new understanding of ovarian cancer prognosis at the single-cell level and offer a reference for therapy decisions for patient treatment.

TRPs in Ovarian Serous Cystadenocarcinoma: The Expression Patterns, Prognostic Roles, and Potential Therapeutic Targets

Ovarian cancer (usually ovarian serous cystadenocarcinoma, or OV) is the fifth leading cause of cancer-related deaths in women, with more than 184,000 deaths reported worldwide annually, and is a highly malignant carcinoma. However, the mechanism of etiology remains unclear. The lack of prognostic and diagnostic biomarkers is a main limitation for clinical diagnosis and treatment. The transient receptor potential (TRP) channels play essential roles in the occurrence and development of cancers which may have the potential as a therapeutic target for OV. In our study, we used bioinformatic methods to study the potential effect and function of the TRP family in patients with OV. Differential expression analysis showed that the expression of TRPC7, TRPV4, and other TRP family members was significantly different between tumor and normal tissues. Through survival analysis, we screened out that the high expression of TRPC7, TRPV4, and TRPM (2,4,8) was negatively correlated with the prognosis of patients. In contrast, the low expression of TRPM3 was negatively associated with the prognosis. Cox regression analysis further indicated that TRPV4 was OV’s most likely therapeutic target. Finally, we conducted mRNA expression analysis, functional enrichment analysis, and immune infiltration analysis to confirm that TRPV4 was the most convincing therapeutic target of OV.

Mechanisms for Host Immune Evasion Mediated by Plasmodium falciparum-Infected Erythrocyte Surface Antigens

Plasmodium falciparum infection causes the most severe form of malaria. It has been hypothesized that P. falciparum directly suppresses host immune responses because sufficient acquired immunity is often not induced even by repeated P. falciparum infections in malaria-endemic areas. It is known that many kinds of P. falciparum-derived proteins are expressed on the surface of P. falciparum-infected erythrocytes (IEs), and these proteins have long been thought to be a key to the elucidation of the host immune evasion mechanisms. Our recent studies have revealed that the P. falciparum-derived erythrocyte surface antigen, RIFIN, the largest multiple gene family protein in the P. falciparum genome, suppresses host immune cell activation through direct interaction with human inhibitory immune receptors. In this review, we will discuss the molecular mechanisms for host immune evasion by P. falciparum-infected erythrocyte surface antigens. In addition, we will discuss the recently identified host immune response to P. falciparum using specialized antibodies that target host-P. falciparum-derived molecule interactions.

The Role of Cancer-Associated Fibroblasts in Ovarian Cancer

Simple Summary

Ovarian cancer is a lethal gynecologic tumor and is generally resistant to conventional treatments. Stable cancer-associated fibroblasts (CAFs) are important cellular components in the ovarian cancer tumor microenvironment and may provide novel resources for future treatment strategies. Different subtypes of CAFs display specific functions in tumor pathogenesis and various CAF markers suggest potential treatment targets. Several clinical or preclinical trials have targeted stromal fibroblasts and focused on the properties of CAFs to enhance ovarian cancer treatment efficacy. This review concentrates on the origins, subtypes, and activation of CAFs, as well as specific roles of CAFs in regulating tumor development and drug resistance, and aims to provide potential and prospective targets for improving the therapeutic efficacy of ovarian cancer treatment.

Abstract

Ovarian cancer is a lethal gynecologic tumor and is generally resistant to conventional treatments. Stable cancer-associated fibroblasts (CAFs) are important cellular components in the ovarian cancer tumor microenvironment and may provide novel resources for future treatment strategies. Different subtypes of CAFs display specific functions in tumor pathogenesis and various CAF markers suggest potential treatment targets, such as FAP and GPR77. Both autocrine and paracrine cytokines play important roles in the CAF activation process and regulate tumor progression. Downstream mediators and pathways, including IL-6, TGF-β, NF-κB, mitogen-activated protein kinase (MAPK), and AKT/mTOR/(p70S6K), play important roles in the initiation, proliferation, invasiveness, and metastasis of ovarian cancer cells and also participate in angiogenesis, therapeutic resistance, and other biological processes. Several clinical or preclinical trials have targeted stromal fibroblasts and focused on the properties of CAFs to enhance ovarian cancer treatment outcomes. This review concentrates on the origins, subtypes, and activation of CAFs, as well as specific roles of CAFs in regulating tumor development and drug resistance, and aims to provide potential and prospective targets for improving the therapeutic efficacy of ovarian cancer treatment.

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.

Recent Advances in Ovarian Cancer: Therapeutic Strategies, Potential Biomarkers, and Technological Improvements

Aggressive and recurrent gynecological cancers are associated with worse prognosis and a lack of effective therapeutic response. Ovarian cancer (OC) patients are often diagnosed in advanced stages, when drug resistance, angiogenesis, relapse, and metastasis impact survival outcomes. Currently, surgical debulking, radiotherapy, and/or chemotherapy remain the mainstream treatment modalities; however, patients suffer unwanted side effects and drug resistance in the absence of targeted therapies. Hence, it is urgent to decipher the complex disease biology and identify potential biomarkers, which could greatly contribute to making an early diagnosis or predicting the response to specific therapies. This review aims to critically discuss the current therapeutic strategies for OC, novel drug-delivery systems, and potential biomarkers in the context of genetics and molecular research. It emphasizes how the understanding of disease biology is related to the advancement of technology, enabling the exploration of novel biomarkers that may be able to provide more accurate diagnosis and prognosis, which would effectively translate into targeted therapies, ultimately improving patients’ overall survival and quality of life.

Three-Dimensional Modelling of Ovarian Cancer: From Cell Lines to Organoids for Discovery and Personalized Medicine

Ovarian cancer has the highest mortality of all of the gynecological malignancies. There are several distinct histotypes of this malignancy characterized by specific molecular events and clinical behavior. These histotypes have differing responses to platinum-based drugs that have been the mainstay of therapy for ovarian cancer for decades. For histotypes that initially respond to a chemotherapeutic regime of carboplatin and paclitaxel such as high-grade serous ovarian cancer, the development of chemoresistance is common and underpins incurable disease. Recent discoveries have led to the clinical use of PARP (poly ADP ribose polymerase) inhibitors for ovarian cancers defective in homologous recombination repair, as well as the anti-angiogenic bevacizumab. While predictive molecular testing involving identification of a genomic scar and/or the presence of germline or somatic BRCA1 or BRCA2 mutation are in clinical use to inform the likely success of a PARP inhibitor, no similar tests are available to identify women likely to respond to bevacizumab. Functional tests to predict patient response to any drug are, in fact, essentially absent from clinical care. New drugs are needed to treat ovarian cancer. In this review, we discuss applications to address the currently unmet need of developing physiologically relevant in vitro and ex vivo models of ovarian cancer for fundamental discovery science, and personalized medicine approaches. Traditional two-dimensional (2D) in vitro cell culture of ovarian cancer lacks critical cell-to-cell interactions afforded by culture in three-dimensions. Additionally, modelling interactions with the tumor microenvironment, including the surface of organs in the peritoneal cavity that support metastatic growth of ovarian cancer, will improve the power of these models. Being able to reliably grow primary tumoroid cultures of ovarian cancer will improve the ability to recapitulate tumor heterogeneity. Three-dimensional (3D) modelling systems, from cell lines to organoid or tumoroid cultures, represent enhanced starting points from which improved translational outcomes for women with ovarian cancer will emerge.

Prognostic utility of the ovarian cancer secretome: a systematic investigation

BACKGROUND

Ovarian cancer is usually detected at an advanced stage with frequent recurrence. The recurrence-free survival and overall survival is influenced by the age at diagnosis, tumor stage and histological subtype. Nonetheless, quantifiable prognostic biomarkers are needed for early identification of the high-risk patients and for personalized medicine. Several studies link tumor-specific dysregulated expression of certain proteins with ovarian cancer prognosis. However, careful investigation of presence of these prognostically relevant proteins in ovarian cancer secretome is lacking.

OBJECTIVE

To critically analyze the recent published data on prognostically relevant proteins for ovarian cancer and to carefully search how many of them are reported in the published ovarian cancer secretome datasets.

DESIGN

A search for relevant studies in the past 2 years was conducted in PubMed and a comprehensive list of proteins associated with the ovarian cancer prognosis was prepared. These were cross-referred to the published ovarian cancer secretome profiles. The proteins identified in the secretome were further shortlisted based on a scoring strategy employing stringent criteria.

RESULTS

A panel of seven promising secretory biomarkers associated with ovarian cancer prognosis is proposed.

CONCLUSION

Scanning the ovarian cancer secretome datasets provides the opportunity to identify if tumor-specific biomarkers could be tested as secretory biomarkers. Detecting their levels in the body fluid would be more advantageous than evaluating the expression in the tissue, since it could be monitored multiple times over the course of the disease to have a better judgment of the prognosis and response to therapy.

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.

Development and Validation of a Six-Gene Prognostic Signature for Bladder Cancer

Human bladder cancer (BCa) is the most common urogenital system malignancy. Patients with BCa have limited treatment efficacy in clinical practice. Novel biomarkers could provide more crucial information conferring to cancer diagnosis, treatment, and prognosis. Here, we aimed to explore and identify novel biomarkers associated with cancer-specific survival of patients with BCa to build a prognostic signature. Based on univariate Cox regression, Lasso regression, and multivariate Cox regression analysis, we conducted an integrated analysis in the training set (GSE32894) and established a six-gene signature to predict the cancer-specific survival for human BCa. The six genes were Cyclin Dependent Kinase 4 (CDK4), E2F Transcription Factor 7 (E2F7), Collagen Type XI Alpha 1 Chain (COL11A1), Bradykinin Receptor B2 (BDKRB2), Yip1 Interacting Factor Homolog B (YIF1B), and Zinc Finger Protein 415 (ZNF415). Then, we validated the prognostic value of the model by using two other datasets (GSE13507 and TCGA). Also, we conducted univariate and multivariate Cox regression analyses, and results indicated that the six-gene signature was an independent prognostic factor of cancer-specific survival of patients with BCa. Functional analysis was performed based on the differentially expressed genes of low- and high-risk patients, and we found that they were enriched in lipid metabolic and cell division-related biological processes. Meanwhile, the gene set enrichment analysis (GSEA) revealed that high-risk samples were enriched in cell cycle and cancer-related pathways [G2/M checkpoint, E2F targets, mitotic spindle, mTOR signaling, spermatogenesis, epithelial–mesenchymal transition (EMT), DNA repair, PI3K/AKT/mTOR signaling, unfolded protein response (UPR), and MYC targets V2]. Lastly, we detected the relative expression of each signature in BCa cell lines by quantitative real-time PCR (qRT-PCR). As far as we know, currently, the present study is the first research that developed and validated a cancer-specific survival prognostic index based on three independent cohorts. The results revealed that this six-gene signature has a predictive ability for cancer-specific prognosis. Moreover, we also verified the relative expression of these six signatures between the bladder cell line and four BCa cell lines by qRT-PCR. Nevertheless, experiments to further explore the function of six genes are lacking.

miR-335 Restrains the Aggressive Phenotypes of Ovarian Cancer Cells by Inhibiting COL11A1

High collagen type XI alpha 1 (COL11A1) levels are associated with tumor progression, chemoresistance, and poor patient survival in several cancer types. MicroRNAs (miRNAs) are dysregulated in multiple cancers, including epithelial ovarian carcinoma (EOC); however, the regulation of COL11A1 by miRNAs in EOC remains unclear. We examined the role of miRNAs in regulating COL11A1 expression. We identified miR-509 and miR-335 as the candidate miRNAs through an online database search. EOC cell treatment with miR-335 mimics abrogated COL11A1 expression and suppressed cell proliferation and invasion, besides increasing the sensitivity of EOC cells to cisplatin. Conversely, treatment with miR-335 inhibitors prompted cell growth/invasiveness and chemoresistance of EOC cells. miR-335 inhibited COL11A1 transcription, thus reducing the invasiveness and chemoresistance of EOC cells via the Ets-1/MMP3 and Akt/c/EBPβ/PDK1 axes, respectively. Furthermore, it did not directly regulate PDK1 but increased PDK1 ubiquitination and degradation through COL11A1 inhibition. In vivo findings highlighted significantly decreased miR-335 mRNA expressions in EOC samples. Furthermore, patients with low miR335 levels were susceptible to advanced-stage cancer, poor response to chemotherapy, and early relapse. This study highlighted the importance of miR-335 in downregulating COL11A1-mediated ovarian tumor progression, chemoresistance, and poor survival and suggested its potential application as a therapeutic target.

COL11A1 promotes esophageal squamous cell carcinoma proliferation and metastasis and is inversely regulated by miR-335-5p

Background

Esophagus squamous cell carcinoma (ESCC) is a sort of cancer that occurs in the esophageal epithelial tissue. This study performed integrated bioinformatics analysis of Gene Expression Omnibus (GEO) datasets GSE32424, GSE29968, and GSE130078. Collagen type XI alpha 1 (COL11A1) was identified as the hub gene in ESCC progression. The involvement of COL11A1 in ESCC development was next determined using in vitro functional tests.

Methods

Hub genes were identified through integrated bioinformatics analysis. The real-time reverse transcription-polymerase chain reaction was implemented for detecting the expression of COL11A1 mRNA in esophageal cancer cells. KYSE-30 cells were transfected using a vector encoding COL11A1. The proliferation of cells was determined using the Cell Counting Kit-8 (CCK-8) assay. Detection of the cell migration and invasion was made through making use of the transwell test. The development of ESCC cells in vivo was evaluated in naked mice. The interplay among COL11A1 and microRNA-335-5p (miR-335-5p) was discovered using a luciferase reporter experiment.

Results

In vitro studies showed the upregulation of COL11A1 in ESCC cell lines obtained from ESCC patients and upregulation of COL11A1 was correlated with poor disease-free survival of ESCC patients, thereby implying an oncogenic involvement of COL11A1 in ESCC. Overexpression of COL11A1 enhanced the proliferation of ESCC cells, invasion, and migration; whereas COL11A1 knockdown impeded the proliferation of ESCC cells, invasion, and migration. Additionally, miRNA pathway analysis in combination with TargetScan’s online prediction and the luciferase reporter assay suggested miR-335-5p targeting and negatively regulating the COL11A1 3' untranslated region (3'UTR) within ESCC cells. MiR-335-5p overexpression diminished the development of ESCC cells. Additionally, co-expression of COL11A1 ameliorated the repressive influence of miR-335-5p overexpression on the growth and metastasis of ESCC cells.

Conclusions

Using comprehensive bioinformatics analysis, the current study identified COL11A1 as an oncogene in ESCC. The mechanistic studies indicated that COL11A1 promoted ESCC cell progression and that miR-335-5p negatively regulated the expression of COL11A1 in ESCC.

Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer

BACKGROUND

Late-stage diagnosis of ovarian cancer, a disease that originates in the ovaries and spreads to the peritoneal cavity, lowers 5-year survival rate from 90% to 30%. Early screening tools that can: i) detect with high specificity and sensitivity before conventional tools such as transvaginal ultrasound and CA-125, ii) use non-invasive sampling methods and iii) longitudinally significantly increase survival rates in ovarian cancer are needed. Studies that employ blood-based screening tools using circulating tumor-cells, -DNA, and most recently tumor-derived small extracellular vesicles (sEVs) have shown promise in non-invasive detection of cancer before standard of care. Our findings in this study show the promise of a sEV-derived signature as a non-invasive longitudinal screening tool in ovarian cancer.

METHODS

Human serum samples as well as plasma and ascites from a mouse model of ovarian cancer were collected at various disease stages. Small extracellular vesicles (sEVs) were extracted using a commercially available kit. RNA was isolated from lysed sEVs, and quantitative RT-PCR was performed to identify specific metastatic gene expression.

CONCLUSION

This paper highlights the potential of sEVs in monitoring ovarian cancer progression and metastatic development. We identified a 7-gene panel in sEVs derived from plasma, serum, and ascites that overlapped with an established metastatic ovarian carcinoma signature. We found the 7-gene panel to be differentially expressed with tumor development and metastatic spread in a mouse model of ovarian cancer. The most notable finding was a significant change in the ascites-derived sEV gene signature that overlapped with that of the plasma-derived sEV signature at varying stages of disease progression. While there were quantifiable changes in genes from the 7-gene panel in serum-derived sEVs from ovarian cancer patients, we were unable to establish a definitive signature due to low sample number. Taken together our findings show that differential expression of metastatic genes derived from circulating sEVs present a minimally invasive screening tool for ovarian cancer detection and longitudinal monitoring of molecular changes associated with progression and metastatic spread.

Modeling the Tumor Microenvironment of Ovarian Cancer: The Application of Self-Assembling Biomaterials

Ovarian cancer (OvCa) is one of the leading causes of gynecologic malignancies. Despite treatment with surgery and chemotherapy, OvCa disseminates and recurs frequently, reducing the survival rate for patients. There is an urgent need to develop more effective treatment options for women diagnosed with OvCa. The tumor microenvironment (TME) is a key driver of disease progression, metastasis and resistance to treatment. For this reason, 3D models have been designed to represent this specific niche and allow more realistic cell behaviors compared to conventional 2D approaches. In particular, self-assembling peptides represent a promising biomaterial platform to study tumor biology. They form nanofiber networks that resemble the architecture of the extracellular matrix and can be designed to display mechanical properties and biochemical motifs representative of the TME. In this review, we highlight the properties and benefits of emerging 3D platforms used to model the ovarian TME. We also outline the challenges associated with using these 3D systems and provide suggestions for future studies and developments. We conclude that our understanding of OvCa and advances in materials science will progress the engineering of novel 3D approaches, which will enable the development of more effective therapies.

Applications of Multi-omics Approaches for Exploring the Molecular Mechanism of Ovarian Carcinogenesis

Ovarian cancer ranks as the fifth most common cause of cancer-related death in females. The molecular mechanisms of ovarian carcinogenesis need to be explored in order to identify effective clinical therapies for ovarian cancer. Recently, multi-omics approaches have been applied to determine the mechanisms of ovarian oncogenesis at genomics (DNA), transcriptomics (RNA), proteomics (proteins), and metabolomics (metabolites) levels. Multi-omics approaches can identify some diagnostic and prognostic biomarkers and therapeutic targets for ovarian cancer, and these molecular signatures are beneficial for clarifying the development and progression of ovarian cancer. Moreover, the discovery of molecular signatures and targeted therapy strategies could noticeably improve the prognosis of ovarian cancer patients.

Peptide Signatures for Prognostic Markers of Pancreatic Cancer by MALDI Mass Spectrometry Imaging

Despite the overall poor prognosis of pancreatic cancer there is heterogeneity in clinical courses of tumors not assessed by conventional risk stratification. This yields the need of additional markers for proper assessment of prognosis and multimodal clinical management. We provide a proof of concept study evaluating the feasibility of Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to identify specific peptide signatures linked to prognostic parameters of pancreatic cancer. On 18 patients with exocrine pancreatic cancer after tumor resection, MALDI imaging analysis was performed additional to histopathological assessment. Principal component analysis (PCA) was used to explore discrimination of peptide signatures of prognostic histopathological features and receiver operator characteristic (ROC) to identify which specific m/z values are the most discriminative between the prognostic subgroups of patients. Out of 557 aligned m/z values discriminate peptide signatures for the prognostic histopathological features lymphatic vessel invasion (pL, 16 m/z values, eight proteins), nodal metastasis (pN, two m/z values, one protein) and angioinvasion (pV, 4 m/z values, two proteins) were identified. These results yield proof of concept that MALDI-MSI of pancreatic cancer tissue is feasible to identify peptide signatures of prognostic relevance and can augment risk assessment.

Heat Shock Protein 27, a Novel Downstream Target of Collagen Type XI alpha 1, Synergizes with Fatty Acid Oxidation to Confer Cisplatin Resistance in Ovarian Cancer Cells

Simple Summary

Collagen type XI alpha 1 (COL11A1) is a novel biomarker associated with poor survival in ovarian cancer and a promoter of ovarian cancer cell resistance to cisplatin. However, it is poorly understood how COL11A1 promotes ovarian cancer cisplatin resistance. We performed assays to discover the biological molecules that are activated by COL11A1 in ovarian cancer cells. We found that heat shock protein 27 (HSP27), a cellular stress response protein, is activated by COL11A1. Furthermore, we observed that depletion and drug inhibition of HSP27 makes ovarian cancer cells grown on COL11A1 to be more susceptible to cisplatin treatment. We also discovered that ovarian cancer cells upregulate fatty acid oxidation (FAO), a metabolic process that breaks down fats to generate energy and biomolecules, to compensate for the loss of HSP27. Our findings have therapeutic implications for clinicians who wish to treat ovarian tumors that maintain high levels of COL11A1 and HSP27.

Abstract

Collagen type XI alpha 1 (COL11A1) is a novel biomarker associated with cisplatin resistance in ovarian cancer. We have previously reported that COL11A1 activates Src-Akt signaling through the collagen receptors discoidin domain receptor 2 (DDR2) and integrin α1β1 to confer cisplatin resistance to ovarian cancer cells. To identify the potential signaling molecules downstream of COL11A1 signaling, we performed protein kinase arrays and identified heat shock protein 27 (HSP27) as a potential mediator of COL11A1-induced cisplatin resistance. Through receptor knockdown and inhibitor experiments, we demonstrated that COL11A1 significantly upregulates HSP27 phosphorylation and expression via DDR2/integrin α1β1 and Src/Akt signaling in ovarian cancer cells. Furthermore, genetic knockdown and pharmacological inhibition of HSP27, via ivermectin treatment, significantly sensitizes ovarian cancer cells cultured on COL11A1 to cisplatin treatment. HSP27 knockdown or inhibition also decreases NFκB activity as well as the expression of inhibitors of apoptosis proteins (IAPs), which are known downstream effector molecules of COL11A1 that promote cisplatin resistance. Interestingly, HSP27 knockdown or inhibition stimulates ovarian cancer cells to upregulate fatty acid oxidation (FAO) for survival and cisplatin resistance, and dual inhibition of HSP27 and FAO synergistically kills ovarian cancer cells that are cultured on COL11A1. Collectively, this study identifies HSP27 as a novel and druggable COL11A1 downstream effector molecule that may be targeted to overcome cisplatin resistance in recurrent ovarian cancer, which often overexpress COL11A1.

Subtyping of head and neck squamous cell cancers based on immune signatures

Although head and neck squamous cell cancer (HNSCC) is one of the cancer types in which immune checkpoint inhibitors (ICIs) has achieved a certain success, only a subset of HNSCC patients respond to ICIs. Thus, identification of HNSCC subtypes responsive to ICIs is crucial. Using hierarchical clustering, we identified three subtypes of HNSCC, termed Immunity-H, Immunity-M, and Immunity-L, based on the enrichment scores of 28 immune cells generated by the single-sample gene-set enrichment analysis of transcriptome data. We demonstrated that this subtyping method was stable and producible in four different HNSCC cohorts. Immunity-H had the highest levels of immune infiltrates and PD-L1 expression, lowest levels of stemness, intratumor heterogeneity and genomic instability, and favorable prognosis. In contrast, Immunity-L had the lowest levels of immune infiltrates and PD-L1 expression, highest levels of stemness, intratumor heterogeneity and genomic instability, and unfavorable prognosis. We found that somatic copy number alteration had a significant negative association with anti-tumor immunity in HNSCC, while tumor mutation burden showed no significant association. TP53, COL11A1, NSD1, and PKHD1L1 were more frequently mutated in Immunity-H versus Immunity-L, and their mutations were associated with increased immune signatures in HNSCC. Besides immune-related pathways, many stromal and oncogenic pathways were highly enriched in Immunity-H, including cell adhesion molecules, focal adhesion, ECM-receptor interaction, calcium signaling, MAPK signaling, apoptosis, VEGF signaling, and PPAR signaling. The high levels of PD-L1 expression and immune infiltration in Immunity-H indicate that this subtype responds best to ICIs. Our study recaptures the immunological heterogeneity in HNSCC and provide clinical implications for the immunotherapy of HNSCC.

An investigation on the c-MYC, AXIN1, and COL11A1 gene expression in colorectal cancer

The high incidence rate of CRC demands early diagnosis of the disease and readiness of diagnostic biomarker. In present study, we have investigated c-MYC, AXIN1, and COL11A1 expression levels in course of CRC progression and their correlation with demographics and clinical risk factors. Fifty-five tumors and 41 normal tissues were obtained from Tumor Bank of Iran, total RNA was extracted, cDNA was synthesized, and RT-qPCR was performed. Results were analyzed using Rest 2009 and SPSS software. Analysis at mRNA level showed upregulation of the two genes; c-MYC with a p-value of 0.001 and COL11A1 with an observed p-value of 0.02, while a p-value of 0.04 indicated AXIN1 downregulation. The observed overexpression of COL11A1 in stage 0 compared to other stages of CRC asserts importance of this gene in CRC prognosis. Moreover, statistical analysis confirms a significant correlation between expression of these genes and several clinical risk factors of CRC. Our study supports the importance of the studied genes and provides further information regarding the molecular mechanism of CRC. Further studies on these genes could elucidate their pivotal role for both early detection and/or diagnosis of CRC in addition to have important biomarkers for CRC management available.

Collagen XI alpha 1 chain, a potential therapeutic target for cancer

Extracellular matrix (ECM) plays an important role in the progression of cancer. Collagen is the most abundant component in ECM, and it is involved in the biological formation of cancer. Although type XI collagen is a minor fibrillar collagen, collagen XI alpha 1 chain (COL11A1) has been found to be upregulated in a variety of cancers including ovarian cancer, breast cancer, thyroid cancer, pancreatic cancer, non-small-cell lung cancer, and transitional cell carcinoma of the bladder. High levels of COL11A1 usually predict poor prognosis, while COL11A1 is related to angiogenesis, invasion, and drug resistance of cancer. However, little is known about the specific mechanism by which COL11A1 regulates tumor progression. Here, we have organized and summarized the recent developments regarding elucidation of the relationship between COL11A1 and various cancers, as well as the interaction between COL11A1 and intracellular signaling pathways. In addition, we have selected therapeutic agents targeting COL11A1. All these indicate the possibility of using COL11A1 as a target for cancer treatment.

Extracellular Matrices and Cancer-Associated Fibroblasts: Targets for Cancer Diagnosis and Therapy?

Solid cancer progression is dictated by neoplastic cell features and pro-tumoral crosstalks with their microenvironment. Stroma modifications, such as fibroblast activation into cancer-associated fibroblasts (CAFs) and extracellular matrix (ECM) remodeling, are now recognized as critical events for cancer progression and as potential therapeutic or diagnostic targets. The recent appreciation of the key, complex and multiple roles of the ECM in cancer and of the CAF diversity, has revolutionized the field and raised innovative but challenging questions. Here, we rapidly present CAF heterogeneity in link with their specific ECM remodeling features observed in cancer, before developing each of the impacts of such ECM modifications on tumor progression (survival, angiogenesis, pre-metastatic niche, chemoresistance, etc.), and on patient prognosis. Finally, based on preclinical studies and recent results obtained from clinical trials, we highlight key mechanisms or proteins that are, or may be, used as potential therapeutic or diagnostic targets, and we report and discuss benefits, disappointments, or even failures, of recently reported stroma-targeting strategies.

High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

BACKGROUND

High-grade serous tubo-ovarian cancer (HGSTOC) is characterised by extensive inter- and intratumour heterogeneity, resulting in persistent therapeutic resistance and poor disease outcome. Molecular subtype classification based on bulk RNA sequencing facilitates a more accurate characterisation of this heterogeneity, but the lack of strong prognostic or predictive correlations with these subtypes currently hinders their clinical implementation. Stromal admixture profoundly affects the prognostic impact of the molecular subtypes, but the contribution of stromal cells to each subtype has poorly been characterised. Increasing the transcriptomic resolution of the molecular subtypes based on single-cell RNA sequencing (scRNA-seq) may provide insights in the prognostic and predictive relevance of these subtypes.

METHODS

We performed scRNA-seq of 18,403 cells unbiasedly collected from 7 treatment-naive HGSTOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. We explored which phenotypic clusters correlated with overall survival based on expression of these transcriptomic markers in microarray data of 1467 tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.

RESULTS

We identified 11 cancer and 32 stromal cell phenotypes in HGSTOC tumours. Of these, the relative frequency of myofibroblasts, TGF-β-driven cancer-associated fibroblasts, mesothelial cells and lymphatic endothelial cells predicted poor outcome, while plasma cells correlated with more favourable outcome. Moreover, we identified a clear cell-like transcriptomic signature in cancer cells, which correlated with worse overall survival in HGSTOC patients. Stromal cell phenotypes differed substantially between molecular subtypes. For instance, the mesenchymal, immunoreactive and differentiated signatures were characterised by specific fibroblast, immune cell and myofibroblast/mesothelial cell phenotypes, respectively. Cell phenotypes correlating with poor outcome were enriched in molecular subtypes associated with poor outcome.

CONCLUSIONS

We used scRNA-seq to identify stromal cell phenotypes predicting overall survival in HGSTOC patients. These stromal features explain the association of the molecular subtypes with outcome but also the latter's weakness of clinical implementation. Stratifying patients based on marker genes specific for these phenotypes represents a promising approach to predict prognosis or response to therapy.