Modification of BRCA1-associated breast cancer risk by HMMR overexpression

Nanoparticulate drug combination inhibits DNA damage repair and PD-L1 expression in BRCA-mutant and wild type triple-negative breast cancer

The high mortality rate associated with metastatic breast cancer presents a significant global challenge. Inherent and chemotherapy-induced DNA damage repair, alongside immunosuppression, drastically contribute to triple-negative breast cancer (TNBC) relapse and metastasis. While poly (ADP-ribose) polymerase (PARP) inhibitors such as olaparib show effectiveness against BRCA1-mutant TNBC, they may lead to drug resistance and reduced efficacy due to increased programmed death-ligand 1 (PD-L1) expression. Our study explored the use of polymer-lipid nanoparticles (PLN) loaded with doxorubicin (DOX) and oligomeric hyaluronic acid (oHA), functionalized iRGD-peptide for integrins targeting (iRGD-DOX-oHA-PLN), to prevent TNBC immunosuppression, DNA repair, and metastasis. The results demonstrate that the iRGD-DOX-oHA-PLNs efficiently downregulated single and double-strand DNA repair proteins and enhanced DNA damage while decreasing PD-L1 expression compared to olaparib. Accordingly, iRGD-DOX-oHA-PLN treatment showed significantly higher efficiency in reducing levels of primary tumor growth and numbers of metastases to the lung and liver compared to olaparib in vitro and in vivo in both BRCA1-mutant and wild type TNBC orthotopic xenograft models.

miR-9-5p/HMMR regulates the tumorigenesis and progression of clear cell renal cell carcinoma through EMT and JAK1/STAT1 signaling pathway

BACKGROUND

The most common malignant type of kidney cancer is clear cell renal cell carcinoma (ccRCC). The expression levels of hyaluronan-mediated motility receptor (HMMR) in many tumor types are significantly elevated. HMMR is closely associated with tumor-related progression, treatment resistance, and poor prognosis, and has yet to be fully investigated in terms of its expression patterns and molecular mechanisms of action in ccRCC. Further research is imperative to elucidate these aspects.

METHODS

We used The Cancer Genome Atlas (TCGA) database to preliminarily investigate HMMR expression and function in ccRCC and the data for 19 samples from the NCBI GEO database (GSE207493) for single-cell analysis. We assessed the differential expression level of HMMR between ccRCC cancerous tissues and their matched non-tumor tissues. Subsequently, a series of in vivo and in vitro experiments were designed to elucidate the biological function of HMMR in ccRCC, including Transwell assays, CCK-8 assays, clone formation assays and subcutaneous xenograft experiments in nude mice. Through bioinformatics analysis, we identified potential microRNAs (miRNAs) that may regulate HMMR, as well as the possible signaling pathways involved. Finally, we conducted a series of cellular functional experiments to validate our hypotheses regarding the HMMR axis.

RESULTS

HMMR expression was significantly up-regulated in tumor tissues of ccRCC patients, and elevated HMMR expression level showed a strong correlation with ccRCC progression and adverse prognoses of patients. Knocking down HMMR inhibited the proliferative and migratory abilities of ccRCC cells, while its overexpression amplified these oncogenic properties. In nude mice model, reduced HMMR expression inhibited ccRCC tumor proliferation in vivo. Furthermore, overexpression of an upstream transcriptional regulator, miR-9-5p, effectively downregulated HMMR expression and thus impeded ccRCC cells proliferation and migration. HMMR might influence ccRCC growth via the Epithelial-Mesenchymal Transition (EMT) pathway and the Janus Kinase 1/Signal Transducer and Activator of Transcription 1 (JAK1/STAT1) pathway.

CONCLUSIONS

HMMR is overexpressed in ccRCC, and there is a significant link between high HMMR expression and tumor progression, as well as poor patient prognosis. Specifically, HMMR could be targeted and inhibited by miR-9-5p and might modulate the tumorigenesis and progression of ccRCC through both EMT and JAK1/STAT1 signaling pathway.

Noncoding RNA Terc-53 and hyaluronan receptor Hmmr regulate aging in mice

One of the basic questions in the aging field is whether there is a fundamental difference between the aging of lower invertebrates and mammals. A major difference between the lower invertebrates and mammals is the abundancy of noncoding RNAs, most of which are not conserved. We have previously identified a noncoding RNA Terc-53 that is derived from the RNA component of telomerase Terc. To study its physiological functions, we generated two transgenic mouse models overexpressing the RNA in wild-type and early-aging Terc-/- backgrounds. Terc-53 mice showed age-related cognition decline and shortened life span, even though no developmental defects or physiological abnormality at an early age was observed, indicating its involvement in normal aging of mammals. Subsequent mechanistic study identified hyaluronan-mediated motility receptor (Hmmr) as the main effector of Terc-53. Terc-53 mediates the degradation of Hmmr, leading to an increase of inflammation in the affected tissues, accelerating organismal aging. adeno-associated virus delivered supplementation of Hmmr in the hippocampus reversed the cognition decline in Terc-53 transgenic mice. Neither Terc-53 nor Hmmr has homologs in C. elegans. Neither do arthropods express hyaluronan. These findings demonstrate the complexity of aging in mammals and open new paths for exploring noncoding RNA and Hmmr as means of treating age-related physical debilities and improving healthspan.

CoGTEx: Unscaled system-level coexpression estimation from GTEx data forecast novel functional gene partners

MOTIVATION

Coexpression estimations are helpful for analysis of pathways, cofactors, regulators, targets, and human health and disease. Ideally, coexpression estimations should consider as many diverse cell types as possible and consider that available data is not uniform across tissues. Importantly, the coexpression estimations accessible today are performed on a "tissue level", which is based on cell type standardized formulations. Little or no attention is paid to overall gene expression levels. The tissue-level estimation assumes that variance expression levels are more important than mean expression levels. Here, we challenge this assumption by estimating a coexpression calculation at the "system level", which is estimated without standardization by tissue, and show that it provides valuable information. We made available a resource to view, download, and analyze both, tissue- and system-level coexpression estimations from GTEx human data.

METHODS

GTEx v8 expression data was globally normalized, batch-processed, and filtered. Then, PCA, clustering, and tSNE stringent procedures were applied to generate 42 distinct and curated tissue clusters. Coexpression was estimated from these 42 tissue clusters computing the correlation of 33,445 genes by sampling 70 samples per tissue cluster to avoid tissue overrepresentation. This process was repeated 20 times, extracting the minimum value provided as a robust estimation. Three metrics were calculated (Pearson, Spearman, and G-statistic) in two data processing modes, at the system-level (TPM scale) and tissue levels (z-score scale).

RESULTS

We first validate our tissue-level estimations compared with other databases. Then, by specific analyses in several examples and literature validations of predictions, we show that system-level coexpression estimation differs from tissue-level estimations and that both contain valuable information reflected in biological pathways. We also show that coexpression estimations are associated to transcriptional regulation. Finally, we present CoGTEx, a valuable resource for viewing and analyzing coexpressed genes in human adult tissues from GTEx v8 data. We introduce our web resource to list, view and explore the coexpressed genes from GTEx data.

CONCLUSION

We conclude that system-level coexpression is a novel and interesting coexpression metric capable of generating plausible predictions and biological hypotheses; and that CoGTEx is a valuable resource to view, compare, and download system- and tissue- level coexpression estimations from GTEx data.

AVAILABILITY

The web resource is available at http://bioinformatics.mx/cogtex.

Black soybean extract inhibits rat mammary carcinogenesis through BRCA1 and TNF-α expression: In silico and in vivo study

Background

Mammary gland carcinoma is a malignant type of cancer that occurs in mammae tissue. Dimethylbenzene (α) anthracene (DMBA) is a carcinogenic agent that causes mammary cancer by damaging cellular DNA. Flavonoids found in the black soybean (Glycine max L. Merr) exhibit anti-carcinogenic effects.

Aim

This study evaluated the anticarcinogenic effects of black soybean extract.

Methods

The activity of flavonoid compounds in black soybean was determined in silico. Five groups of rats, four in each group, were established, consisting of a negative control, a positive control, and three treatment groups. Treatment included black soybean extract administration (i.e., T1 = 200, T2 = 400, and T3 = 800 mg of black soybean extract/kg body weight for 10 days). The observed parameters included the immunohistochemical analysis of Breast Cancer 1(BRCA1) and TNF-α.

Results

Based on an in silico study, compounds from black soybeans are non-toxic. Functional annotation analysis revealed that most of the target proteins have a role in biological processes associated with cancer development. An in vivo analysis using an animal mammae cancer model indicated that black soybean extracts inhibited mammae cancer progression by attenuating TNF-α and BRCA1 expression.

Conclusion

The most effective dosage of black soybean extract was 200 mg/kg body weight. An increase in BRCA1 and TNF-α expression may be related to the effects of catechin, daidzein, genistein, and glycitein, which are present in black soybeans.

Hyaluronic acid metabolism and chemotherapy resistance: recent advances and therapeutic potential

Hyaluronic acid (HA) is a major component of the extracellular matrix, providing essential mechanical scaffolding for cells and, at the same time, mediating essential biochemical signals required for tissue homeostasis. Many solid tumors are characterized by dysregulated HA metabolism, resulting in increased HA levels in cancer tissues. HA interacts with several cell surface receptors, such as cluster of differentiation 44 and receptor for hyaluronan-mediated motility, thus co-regulating important signaling pathways in cancer development and progression. In this review, we describe the enzymes controlling HA metabolism and its intracellular effectors emphasizing their impact on cancer chemotherapy resistance. We will also explore the current and future prospects of HA-based therapy, highlighting the opportunities and challenges in the field.

Elevated RHAMM as a biomarker for predicting diabetic kidney disease in patients with type 2 diabetes

Background

Diabetic kidney disease (DKD) poses a significant challenge globally as a complication of diabetes. Hyaluronan (HA), a critical non-sulfated glycosaminoglycan in the extracellular matrix, plays a pivotal role in the progression of DKD. This study assesses the predictive significance of HA's corresponding receptor, RHAMM (receptor for HA-mediated motility), in DKD pathogenesis in type 2 diabetes (T2DM) patients.

Methods

Enzyme-linked immunosorbent assays were utilized to measure plasma and urine levels of HA, CD44 and RHAMM in 99 diabetic patients. Immunohistochemistry staining was employed to examine HA deposition, CD44 and RHAMM expressions from 18 biopsy-proven DKD patients. Spearman correlation analysis, linear regression and receiver operating characteristic (ROC) analysis were conducted to establish associations between plasma HA, CD44 and RHAMM levels, and clinical parameters in DKD patients with T2DM.

Results

Elevated plasma and urine HA, CD44 and RHAMM levels were notably observed in the severe renal dysfunction group. Plasma RHAMM exhibited positive correlations with HA (r = 0.616, P < .001) and CD44 (r = 0.220, P < .001), and a negative correlation with estimated glomerular filtration rate (eGFR) (r = -0.618, P < .001). After adjusting for other potential predictors, plasma RHAMM emerged as an independent predictor of declining eGFR (β = -0.160, P < .05). Increased HA, CD44 and RHAMM levels in kidney biopsies of DKD patients were closely associated with heightened kidney injury. The ROC curve analysis highlighted an area under the curve (AUC) of 0.876 for plasma RHAMM, indicating superior diagnostic efficacy compared to CD44 in predicting DKD pathogenesis. The combined AUC of 0.968 for plasma RHAMM, HA and CD44 also suggested even greater diagnostic potential for DKD pathogenesis.

Conclusion

These findings provide initial evidence that elevated RHAMM levels predict DKD pathogenesis in T2DM patients. The formation of a triple complex involving HA, CD44 and RHAMM on the cell surface shows promise as a targetable biomarker for early intervention to mitigate severe renal dysfunctions.

Integrated bulk and single-cell RNA sequencing identifies an aneuploidy-based gene signature to predict sensitivity of lung adenocarcinoma to traditional chemotherapy drugs and patients' prognosis

Background

Patients with lung adenocarcinoma (LUAD) often develop a poor prognosis. Currently, researches on prognostic and immunotherapeutic capacity of aneuploidy-related genes in LUAD are limited.

Methods

Genes related to aneuploidy were screened based on bulk RNA sequencing data from public databases using Spearman method. Next, univariate Cox and Lasso regression analyses were performed to establish an aneuploidy-related riskscore (ARS) model. Results derived from bioinformatics analysis were further validated using cellular experiments. In addition, typical LUAD cells were identified by subtype clustering, followed by SCENIC and intercellular communication analyses. Finally, ESTIMATE, ssGSEA and CIBERSORT algorithms were employed to analyze the potential relationship between ARS and tumor immune environment.

Results

A five-gene ARS signature was developed. These genes were abnormally high-expressed in LUAD cell lines, and in particular the high expression of CKS1B promoted the proliferative, migratory and invasive phenotypes of LUAD cell lines. Low ARS group had longer overall survival time, higher degrees of inflammatory infiltration, and could benefit more from receiving immunotherapy. Patients in low ASR group responded more actively to traditional chemotherapy drugs (Erlotinib and Roscovitine). The scRNA-seq analysis annotated 17 cell subpopulations into seven cell clusters. Core transcription factors (TFs) such as CREB3L1 and CEBPD were enriched in high ARS cell group, while TFs such as BCLAF1 and UQCRB were enriched in low ARS cell group. CellChat analysis revealed that high ARS cell groups communicated with immune cells via SPP1 (ITGA4-ITGB1) and MK (MDK-NCl) signaling pathways.

Conclusion

In this research, integrative analysis based on the ARS model provided a potential direction for improving the diagnosis and treatment of LUAD.

CD44 and RHAMM Are Microenvironmental Sensors with Dual Metastasis Promoter and Suppressor Functions

The progression of primary tumors to metastases remains a significant roadblock to the treatment of most cancers. Emerging evidence has identified genes that specifically affect metastasis and are potential therapeutic targets for managing tumor progression. However, these genes can have dual tumor promoter and suppressor functions that are contextual in manifestation, and that complicate their development as targeted therapies. CD44 and RHAMM/HMMR are examples of multifunctional proteins that can either promote or suppress metastases, as demonstrated in experimental models. These two proteins can be viewed as microenvironmental sensors and this minireview addresses the known mechanistic underpinnings that may determine their metastasis suppressor versus promoter functions. Leveraging this mechanistic knowledge for CD44, RHAMM, and other multifunctional proteins is predicted to improve the precision of therapeutic targeting to achieve more effective management of metastasis.

Coupled scRNA-seq and Bulk-seq reveal the role of HMMR in hepatocellular carcinoma

Background

Hyaluronan-mediated motility receptor (HMMR) is overexpressed in multiple carcinomas and influences the development and treatment of several cancers. However, its role in hepatocellular carcinoma (HCC) remains unclear.

Methods

The "limma" and "GSVA" packages in R were used to perform differential expression analysis and to assess the activity of signalling pathways, respectively. InferCNV was used to infer copy number variation (CNV) for each hepatocyte and "CellChat" was used to analyse intercellular communication networks. Recursive partitioning analysis (RPA) was used to re-stage HCC patients. The IC50 values of various drugs were evaluated using the "pRRophetic" package. In addition, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to confirm HMMR expression in an HCC tissue microarray. Flow cytometry (FCM) and cloning, Edu and wound healing assays were used to explore the capacity of HMMR to regulate HCC tumour.

Results

Multiple cohort studies and qRT-PCR demonstrated that HMMR was overexpressed in HCC tissue compared with normal tissue. In addition, HMMR had excellent diagnostic performance. HMMR knockdown inhibited the proliferation and migration of HCC cells in vitro. Moreover, high HMMR expression was associated with "G2M checkpoint" and "E2F targets" in bulk RNA and scRNA-seq, and FCM confirmed that HMMR could regulate the cell cycle. In addition, HMMR was involved in the regulation of the tumour immune microenvironment via immune cell infiltration and intercellular interactions. Furthermore, HMMR was positively associated with genomic heterogeneity with patients with high HMMR expression potentially benefitting more from immunotherapy. Moreover, HMMR was associated with poor prognosis in patients with HCC and the re-staging by recursive partitioning analysis (RPA) gave a good prognosis prediction value and could guide chemotherapy and targeted therapy.

Conclusion

The results of the present study show that HMMR could play a role in the diagnosis, prognosis, and treatments of patients with HCC based on bulk RNA-seq and scRAN-seq analyses and is a promising molecular marker for HCC.

Exploring HMMR as a therapeutic frontier in breast cancer treatment, its interaction with various cell cycle genes, and targeting its overexpression through specific inhibitors

Among women, breast carcinoma is one of the most complex cancers, with one of the highest death rates worldwide. There have been significant improvements in treatment methods, but its early detection still remains an issue to be resolved. This study explores the multifaceted function of hyaluronan-mediated motility receptor (HMMR) in breast cancer progression. HMMR's association with key cell cycle regulators (AURKA, TPX2, and CDK1) underscores its pivotal role in cancer initiation and advancement. HMMR's involvement in microtubule assembly and cellular interactions, both extracellularly and intracellularly, provides critical insights into its contribution to cancer cell processes. Elevated HMMR expression triggered by inflammatory signals correlates with unfavorable prognosis in breast cancer and various other malignancies. Therefore, recognizing HMMR as a promising therapeutic target, the study validates the overexpression of HMMR in breast cancer and various pan cancers and its correlation with certain proteins such as AURKA, TPX2, and CDK1 through online databases. Furthermore, the pathways associated with HMMR were explored using pathway enrichment analysis, such as Gene Ontology, offering a foundation for the development of effective strategies in breast cancer treatment. The study further highlights compounds capable of inhibiting certain pathways, which, in turn, would inhibit the upregulation of HMMR in breast cancer. The results were further validated via MD simulations in addition to molecular docking to explore protein-protein/ligand interaction. Consequently, these findings imply that HMMR could play a pivotal role as a crucial oncogenic regulator, highlighting its potential as a promising target for the therapeutic intervention of breast carcinoma.

The Mayo Clinic Salivary Tissue-Organoid Biobanking: A Resource for Salivary Regeneration Research

The salivary gland (SG) is an essential organ that secretes saliva, which supports versatile oral function throughout life, and is maintained by elusive epithelial stem and progenitor cells (SGSPC). Unfortunately, aging, drugs, autoimmune disorders, and cancer treatments can lead to salivary dysfunction and associated health consequences. Despite many ongoing therapeutic efforts to mediate those conditions, investigating human SGSPC is challenging due to lack of standardized tissue collection, limited tissue access, and inadequate purification methods. Herein, we established a diverse and clinically annotated salivary regenerative biobanking at the Mayo Clinic, optimizing viable salivary cell isolation and clonal assays in both 2D and 3D-matrigel growth environments. Our analysis identified ductal epithelial cells in vitro enriched with SGSPC expressing the CD24/EpCAM/CD49f+ and PSMA- phenotype. We identified PSMA expression as a reliable SGSPC differentiation marker. Moreover, we identified progenitor cell types with shared phenotypes exhibiting three distinct clonal patterns of salivary differentiation in a 2D environment. Leveraging innovative label-free unbiased LC-MS/MS-based single-cell proteomics, we identified 819 proteins across 71 single cell proteome datasets from purified progenitor-enriched parotid gland (PG) and sub-mandibular gland (SMG) cultures. We identified distinctive co-expression of proteins, such as KRT1/5/13/14/15/17/23/76 and 79, exclusively observed in rare, scattered salivary ductal basal cells, indicating the potential de novo source of SGSPC. We also identified an entire class of peroxiredoxin peroxidases, enriched in PG than SMG, and attendant H2O2-dependent cell proliferation in vitro suggesting a potential role for PRDX-dependent floodgate oxidative signaling in salivary homeostasis. The distinctive clinical resources and research insights presented here offer a foundation for exploring personalized regenerative medicine.

Functional annotation with expression validation identifies novel metastasis-relevant genes from post-GWAS risk loci in sporadic colorectal carcinomas

BACKGROUND

Colorectal cancer (CRC) is the third highest incidence cancer and is the leading cause of cancer mortality worldwide. Metastasis to distal organ is the major cause of cancer mortality. However, the underlying genetic factors are unclear. This study aimed to identify metastasis-relevant genes and pathways for better management of metastasis-prone patients.

METHODS

A case-case genome-wide association study comprising 2677 sporadic Chinese CRC cases (1282 metastasis-positive vs 1395 metastasis-negative) was performed using the Human SNP6 microarray platform and analysed with the correlation/trend test based on the additive model. SNP variants with association testing -log10 p value ≥5 were imported into Functional Mapping and Annotation (FUMA) for functional annotation.

RESULTS

Glycolysis was uncovered as the top hallmark gene set. Transcripts from two of the five genes profiled, hematopoietic substrate 1 associated protein X 1 (HAX1) and hyaluronan-mediatedmotility receptor (HMMR), were significantly upregulated in the metastasis-positive tumours. In contrast to disease-risk variants, HAX1 appeared to act synergistically with HMMR in significantly impacting metastasis-free survival. Examining the subtype datasets with FUMA and Ingenuity Pathway Analysis (IPA) identified distinct pathways demonstrating sexual dimorphism in CRC metastasis.

CONCLUSIONS

Combining genome-wide association testing with in silico functional annotation and wet-bench validation identified metastasis-relevant genes that could serve as features to develop subtype-specific metastasis-risk signatures for tailored management of patients with stage I-III CRC.

Biological basis of extensive pleiotropy between blood traits and cancer risk

BACKGROUND

The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations.

METHODS

Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis.

RESULTS

The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood-cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis.

CONCLUSIONS

This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk.

Identification and validation of a 4-extracellular matrix gene signature associated with prognosis and immune infiltration in lung adenocarcinoma

Background

The extracellular matrix (ECM) plays a crucial role in the development and tumor microenvironment of lung adenocarcinoma (LUAD). This study aimed to establish a risk score of ECM-related genes in LUAD and explore the association between the risk score and patient survival as well as immune cell infiltration, somatic mutations, and therapy response.

Methods

Gene expression data from The Cancer Genome Atlas (TGCA) and eight Gene Expression Omnibus (GEO) databases were used to analyze and identify differentially expressed genes (DEGs). Prognostic ECM-related genes were identified and utilized to formulate a prognostic signature. A nomogram was constructed using TCGA dataset and validated in two GEO datasets. Differences between high- and low-risk patients were analyzed for function enrichment, immune cell infiltration, somatic mutations, and therapy response. Finally, Quantitative real-time PCR (qRT-PCR) was used to detect the mRNA expression of DEGs in LUAD.

Results

A risk score based on four ECM-related genes, ANOS1, CD36, COL11A1, and HMMR, was identified as an independent prognostic factor for overall survival (OS) compared to other clinical variables. Subsequently, a nomogram incorporating the risk score and TNM staging was developed using the TCGA dataset. Internal and external validation of the nomogram, conducted through calibration plots, C-index, time-dependent receiver operating characteristics (ROC), integrated discrimination improvement (IDI), and decision curve analyses (DCA), demonstrated the excellent discriminatory ability and clinical practicability of this nomogram. The risk score correlated with the distribution of function enrichment, immune cell infiltration, and immune checkpoint expression. More somatic mutations occurred in the high-risk group. The risk score also demonstrated a favorable ability to predict immunotherapy response and drug sensitivity.

Conclusion

A novel signature based on four ECM-related genes is developed to help predict LUAD prognosis. This signature correlates with tumor immune microenvironment and can predict the response to different therapies in LUAD patients.

FIGNL1 Promotes Hepatocellular Carcinoma Formation via Remodeling ECM-receptor Interaction Pathway Mediated by HMMR

BACKGROUND

The development of novel biomarkers is crucial for the treatment of HCC. In this study, we investigated a new molecular therapeutic target for HCC. Fidgetin-like 1 (FIGNL1) has been reported to play a vital role in lung adenocarcinoma. However, the potential function of FIGNL1 in HCC is still unknown.

OBJECTIVE

This study aims to investigate the key regulatory mechanisms of FIGNL1 in the formation of HCC.

METHODS

The regulatory effect of FIGNL1 on HCC was studied by lentivirus infection. In vitro, the effects of FIGNL1 on the proliferation, migration and apoptosis of cells were investigated by CCK8, colony formation assay, transwell and flow cytometry. Meanwhile, the regulation of FIGNL1 on HCC formation in vivo was studied by subcutaneous transplanted tumors. In addition, using transcriptome sequencing technology, we further explored the specific molecular mechanism of FIGNL1 regulating the formation of HCC.

RESULTS

Functionally, we demonstrated that FIGNL1 knockdown significantly inhibited HCC cell proliferation, migration and promoted cell apoptosis in vitro. Similarly, the knockdown of FIGNL1 meaningfully weakened hepatocarcinogenesis in nude mice. Transcriptome sequencing revealed that FIGNL1 affected the expression of genes involved in extracellular matrix-receptor (ECM-receptor) interaction pathway, such as hyaluronan mediated motility receptor (HMMR). Further validation found that overexpression of HMMR based on knockdown FIGNL1 can rescue the expression abundance of related genes involved in the ECM-receptor interaction pathway.

CONCLUSION

Our study revealed that FIGNL1 could modulate the ECM-receptor interaction pathway through the regulation of HMMR, thus regulating the formation of HCC.

At the Crossroads of the cGAS-cGAMP-STING Pathway and the DNA Damage Response: Implications for Cancer Progression and Treatment

The evolutionary conserved DNA-sensing cGAS-STING innate immunity pathway represents one of the most important cytosolic DNA-sensing systems that is activated in response to viral invasion and/or damage to the integrity of the nuclear envelope. The key outcome of this pathway is the production of interferon, which subsequently stimulates the transcription of hundreds of genes. In oncology, the situation is complex because this pathway may serve either anti- or pro-oncogenic roles, depending on context. The prevailing understanding is that when the innate immune response is activated by sensing cytosolic DNA, such as DNA released from ruptured micronuclei, it results in the production of interferon, which attracts cytotoxic cells to destroy tumors. However, in tumor cells that have adjusted to significant chromosomal instability, particularly in relapsed, treatment-resistant cancers, the cGAS-STING pathway often supports cancer progression, fostering the epithelial-to-mesenchymal transition (EMT). Here, we review this intricate pathway in terms of its association with cancer progression, giving special attention to pancreatic ductal adenocarcinoma and gliomas. As the development of new cGAS-STING-modulating small molecules and immunotherapies such as oncolytic viruses involves serious challenges, we highlight several recent fundamental discoveries, such as the proton-channeling function of STING. These discoveries may serve as guiding lights for potential pharmacological advancements.

HMMR alleviates endoplasmic reticulum stress by promoting autophagolysosomal activity during endoplasmic reticulum stress-driven hepatocellular carcinoma progression

BACKGROUND

The mechanism of hepatitis B virus (HBV)-induced carcinogenesis remains an area of interest. The accumulation of hepatitis B surface antigen in the endoplasmic reticulum (ER) of hepatocytes stimulates persistent ER stress. Activity of the unfolded protein response (UPR) pathway of ER stress may play an important role in inflammatory cancer transformation. How the protective UPR pathway is hijacked by cells as a tool for malignant transformation in HBV-related hepatocellular carcinoma (HCC) is still unclear. Here, we aimed to define the key molecule hyaluronan-mediated motility receptor (HMMR) in this process and explore its role under ER stress in HCC development.

METHODS

An HBV-transgenic mouse model was used to characterize the pathological changes during the tumor progression. Proteomics and transcriptomics analyses were performed to identify the potential key molecule, screen the E3 ligase, and define the activation pathway. Quantitative real-time PCR and Western blotting were conducted to detect the expression of genes in tissues and cell lines. Luciferase reporter assay, chromatin immunoprecipitation, coimmunoprecipitation, immunoprecipitation, and immunofluorescence were employed to investigate the molecular mechanisms of HMMR under ER stress. Immunohistochemistry was used to clarify the expression patterns of HMMR and related molecules in human tissues.

RESULTS

We found sustained activation of ER stress in the HBV-transgenic mouse model of hepatitis-fibrosis-HCC. HMMR was transcribed by c/EBP homologous protein (CHOP) and degraded by tripartite motif containing 29 (TRIM29) after ubiquitination under ER stress, which caused the inconsistent expression of mRNA and protein. Dynamic expression of TRIM29 in the HCC progression regulated the dynamic expression of HMMR. HMMR could alleviate ER stress by increasing autophagic lysosome activity. The negative correlation between HMMR and ER stress, positive correlation between HMMR and autophagy, and negative correlation between ER stress and autophagy were verified in human tissues.

CONCLUSIONS

This study identified the complicated role of HMMR in autophagy and ER stress, that HMMR controls the intensity of ER stress by regulating autophagy in HCC progression, which could be a novel explanation for HBV-related carcinogenesis.

RHAMM regulates MMTV-PyMT-induced lung metastasis by connecting STING-dependent DNA damage sensing to interferon/STAT1 pro-apoptosis signaling

BACKGROUND

RHAMM is a multifunctional protein that is upregulated in breast tumors, and the presence of strongly RHAMM+ve cancer cell subsets associates with elevated risk of peripheral metastasis. Experimentally, RHAMM impacts cell cycle progression and cell migration. However, the RHAMM functions that contribute to breast cancer metastasis are poorly understood.

METHODS

We interrogated the metastatic functions of RHAMM using a loss-of-function approach by crossing the MMTV-PyMT mouse model of breast cancer susceptibility with Rhamm-/- mice. In vitro analyses of known RHAMM functions were performed using primary tumor cell cultures and MMTV-PyMT cell lines. Somatic mutations were identified using a mouse genotyping array. RNA-seq was performed to identify transcriptome changes resulting from Rhamm-loss, and SiRNA and CRISPR/Cas9 gene editing was used to establish cause and effect of survival mechanisms in vitro.

RESULTS

Rhamm-loss does not alter initiation or growth of MMTV-PyMT-induced primary tumors but unexpectedly increases lung metastasis. Increased metastatic propensity with Rhamm-loss is not associated with obvious alterations in proliferation, epithelial plasticity, migration, invasion or genomic stability. SNV analyses identify positive selection of Rhamm-/- primary tumor clones that are enriched in lung metastases. Rhamm-/- tumor clones are characterized by an increased ability to survive with ROS-mediated DNA damage, which associates with blunted expression of interferon pathway and target genes, particularly those implicated in DNA damage-resistance. Mechanistic analyses show that ablating RHAMM expression in breast tumor cells by siRNA knockdown or CRISPR-Cas9 gene editing blunts interferon signaling activation by STING agonists and reduces STING agonist-induced apoptosis. The metastasis-specific effect of RHAMM expression-loss is linked to microenvironmental factors unique to tumor-bearing lung tissue, notably high ROS and TGFB levels. These factors promote STING-induced apoptosis of RHAMM+ve tumor cells to a significantly greater extent than RHAMM-ve comparators. As predicted by these results, colony size of Wildtype lung metastases is inversely related to RHAMM expression.

CONCLUSION

RHAMM expression-loss blunts STING-IFN signaling, which offers growth advantages under specific microenvironmental conditions of lung tissue. These results provide mechanistic insight into factors controlling clonal survival/expansion of metastatic colonies and has translational potential for RHAMM expression as a marker of sensitivity to interferon therapy.

Guidelines on lung adenocarcinoma prognosis based on immuno-glycolysis-related genes

OBJECTIVES

This study developed a new model for risk assessment of immuno-glycolysis-related genes for lung adenocarcinoma (LUAD) patients to predict prognosis and immunotherapy efficacy.

METHODS

LUAD samples and data obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases are used as training and test columns, respectively. Twenty-two (22) immuno-glycolysis-related genes were screened, the patients diagnosed with LUAD were divided into two molecular subtypes by consensus clustering of these genes. The initial prognosis model was developed using the multiple regression analysis method and Receiver Operating characteristic (ROC) analysis was used to verify its predictive potential. Gene set enrichment analysis (GSEA) showed the immune activities and pathways in different risk populations, we calculated immune checkpoints, immune escape, immune phenomena (IPS), and tumor mutation burden (TMB) based on TCGA datasets. Finally, the relationship between the model and drug sensitivity was analyzed.

RESULTS

Fifteen (15) key differentially expressed genes (DEGs) with prognostic value were screened and a new prognostic model was constructed. Four hundred and forty-three (443) samples were grouped into two different risk cohorts based on median model risk values. It was observed that survival rates in high-risk groups were significantly low. ROC curves were used to evaluate the model's accuracy in determining the survival time and clinical outcome of LUAD patients. Cox analysis of various clinical factors proved that the risk score has great potential as an independent prognostic factor. The results of immunological analysis can reveal the immune infiltration and the activity of related functions in different pathways in the two risk groups, and immunotherapy was more effective in low-risk patients. Most chemotherapeutic agents are more sensitive to low-risk patients, making them more likely to benefit.

CONCLUSION

A novel prognostic model for LUAD patients was established based on IGRG, which could more accurately predict the prognosis and an effective immunotherapy approach for patients.

Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools

Breast cancer (BC) remains the leading cause of cancer-related death in women worldwide. The development of new targeted therapies that may improve patient survival remains an area of growing interest. This study aimed to identify new biomarkers involved in BC progression that could be used as potential targeted therapies. DEGs were selected from three gene expression profiles, GSE55715, GSE124646, and GSE87049, using the GEO2R tool and Venn diagram software. Gene Ontology and KEGG pathways were then performed using DAVID software. Next, the PPI network was constructed using STRING and visualized using Cytoscape software, and hub genes were extracted using the cytoHubba plug-in. Survival analysis was performed using the Kaplan-Meier Plotter, while the expression of hub genes in BC was verified using the GEPIA2 tool. Finally, transcription the factors of hub genes were determined using the NetworkAnalyst database, and the TIMER tool was employed to explore the infiltration levels of tumor immune cells with related genes. A total of 146 DEGs were identified in the three datasets, including 60 upregulated genes that were enriched in the cell cycle, and 86 downregulated genes that were mainly enriched in the TNF signaling pathway and pathways in cancer. Ten genes were identified: BUB1, CDK1, HMMR, MAD2L1, CEP55, AURKA, CCNB2, TPX2, MELK, and KIF20A. The overexpression of hub genes, except CDK1, was associated with poor survival in BC and was regulated by several transcription factors involved in DNA binding activity and transcription regulation. The infiltration levels of immune cells were positively correlated with hub genes, particularly macrophages and CD4+ T cells. This study identified new reliable molecular biomarkers that can serve as potential therapeutic targets for BC treatment.

Hsa_circ_0005273 acts as a sponge of miR-509-3p to promote the malignant behaviors of breast cancer by regulating HMMR expression

BACKGROUND

Breast cancer (BC) is a common malignant tumor that threatens the health of women worldwide. Hsa_circ_0005273 has been identified as a carcinogenic factor in some solid tumors, including BC. However, the molecular mechanism of circ_0005273 in BC is poorly defined.

METHODS

The expression of circ_0005273, miR-509-3p, and hyaluronan-mediated motility receptor (HMMR) mRNA in BC was detected by quantitative real-time polymerase chain reaction. Cell proliferation, migration, invasion, and apoptosis were detected by 5-ethynyl-2'-deoxyuridine, transwell, and flow cytometry assays. The glycolysis level was detected via specific kits. Western blot was used to detect protein expression. Binding between miR-509-3p and circ_0005273 or HMMR was also verified by dual-luciferase reporter, RNA pull-down, and RNA immunoprecipitation assays. Xenograft tumor model was used to detect tumor changes in mice, and immunohistochemistry assay was employed to detect Ki-67 abundance.

RESULTS

Circ_0005273 was increased in BC tissues and cells. Circ_0005273 knockdown might inhibit BC cell proliferation, migration, invasion, glutamine metabolism, and induce apoptosis. Circ_0005273 was a miR-509-3p, and the repression role of circ_0005273 absence on BC cell development was weakened by miR-509-3p inhibitor or HMMR overexpression. Circ_0005273 up-regulated the expression of HMMR by sponging miR-509-3p. Additionally, circ_0005273 silencing might hinder tumor growth in vivo.

CONCLUSION

Circ_0005273 knockdown might repress BC cell malignant behaviors by regulating the miR-509-3p/HMMR axis, which might provide a potential therapeutic target for BC.

Exploring the causality and pathogenesis of systemic lupus erythematosus in breast cancer based on Mendelian randomization and transcriptome data analyses

Introduction

There has been a cumulative interest in relationships between systemic lupus erythematosus (SLE) and cancer risk. Breast cancer is the most common cancer among women worldwide. However, the casual association and pathogenesis between SLE and breast cancer remains incompletely unknown.

Methods

Mendelian randomization (MR) analysis was first conducted to investigate the potential causality between SLE and breast cancer. Sensitivity analyses were applied to validate the reliability of MR results. Transcriptomic data analyses based on the Cancer Genome Atlas and Gene Expression Omnibus databases were then performed to identify and construct a SLE-related gene signature (SLEscore).

Results

The MR analysis demonstrated that genetic predisposition to SLE was casually associated with the decreased risk of breast cancer in the East Asian cohort (odds ratios: 0.95, 95% confidence interval: 0.92-0.98, p=0.006). However, no casual associations were observed in the European population. Furthermore, sensitivity analyses proved the robustness of the present MR results. A prognostic SLEscore consisting of five SLE-related genes (RACGAP1, HMMR, TTK, TOP2A, and KIF15) could distribute patients with breast cancer into the high- and low-risk groups according to survival rates with good predictive ability (p < 0.05).

Conclusion

Our MR study provided evidence that genetic changes in SLE were significantly associated with the decreased risk of breast cancer in the East Asian population, while no causality was found in the European cohorts. Transcriptome data analyses indicated that the SLEscore could serve as a novel biomarker for predicting prognosis when breast cancer and SLE coexisted in patients.

HMMR associates with immune infiltrates and acts as a prognostic biomaker in lung adenocarcinoma

BACKGROUND

To explore the expression of hyaluronan mediated motility receptor (HMMR) in lung adenocarcinoma (LUAD) and its relationship with clinicopathological features and tumor-infiltrating is not clear.

METHODS

The expression of HMMR in Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA)-LUAD. TCGA was employed to examine the relationship between the clinicopathological characteristics and HMMR expression and the LUAD patients' prognosis. Tumor Immune Estimation Resource (TIMER)database was employed to analyze the relationship between immune infiltration and HMMR. Gene Set Enrichment Analysis was explored through gene enrichment. Gene Expression Omnibus (GEO) data and our hospital data were utilized to confirm the findings.

RESULTS

The expression level of HMMR in lung adenocarcinoma tissue and cells was greater than that in the normal group, which was linked to clinical stage, smoking history, and recurrence, and could increase the progression or recurrence of LUAD. Patients in the pathological grade had a significant expression of HMMR in moderately differentiated LUAD tissues. In addition, HMMR has an impact on LUAD patients' overall survival rate [P = 9.5e-06; hazard ratio (HR) = 2]. The level of HMMR expression in LUAD was significantly linked to neutrophils, CD8+T, and CD4+T cells. TMB analysis showed that HMMR could also affect the tumor microenvironment in LUAD. HMMR might be employed as an independent predictive biomarker of LUAD, according to a multivariate COX regression analysis. The findings of GSEA analysis showed that the samples with high HMMR expression levels were rich in cell cycle, cell metabolism, and DNA replication. The analysis results of GSE31210 data are basically consistent with those of TCGA-LUAD.

CONCLUSIONS

It is suggested that HMMR has an effect on the occurrence and development of lung adenocarcinoma. Besides, HMMR is also linked to the level of immune infiltration of neutrophils, CD8+T cells, and CD4+T cells and LUAD patients' prognosis. HMMR was suggested to be utilized as a biomarker or therapeutic target to judge the prognosis and immune infiltration of LUAD.

Screening of the Key Genes for the Progression of Liver Cirrhosis to Hepatocellular Carcinoma Based on Bioinformatics

Hepatocellular carcinoma (HCC), which is among the most globally prevalent cancers, is strongly associated with liver cirrhosis. Using a bioinformatics approach, we have identified and investigated the hub genes responsible for the progression of cirrhosis into HCC. We analyzed the Gene Expression Omnibus (GEO) microarray datasets, GSE25097 and GSE17549, to identify differentially expressed genes (DEGs) in these two conditions and also performed protein-protein interaction (PPI) network analysis. STRING database and Cytoscape software were used to analyze the modules and locate hub genes following which the connections between hub genes and the transition from cirrhosis to HCC, progression of HCC, and prognosis of HCC were investigated. We used the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to detect the molecular mechanisms underlying the action of the primary hub genes. In all, 239 DEGs were obtained, with 94 of them showing evidence of upregulation and 145 showing evidence of downregulation in HCC tissues as compared to cirrhotic liver tissues. We identified six hub genes, namely, BUB1B, NUSAP1, TTK, HMMR, CCNA2, and KIF2C, which were upregulated and had a high diagnostic value for HCC. Besides, these six hub genes were positively related to immune cell infiltration. Since these genes may play a direct role in the progression of cirrhosis to HCC, they can be considered as potential novel molecular indicators for the onset and development of HCC.

The role of RHAMM in cancer: Exposing novel therapeutic vulnerabilities

Receptor for hyaluronic acid-mediated motility (RHAMM) is a cell surface receptor for hyaluronic acid that is critical for cell migration and a cell cycle protein involved in microtubule assembly and stability. These functions of RHAMM are required for cellular stress responses and cell cycle progression but are also exploited by tumor cells for malignant progression and metastasis. RHAMM is often overexpressed in tumors and is an independent adverse prognostic factor for a number of cancers such as breast and prostate. Interestingly, pharmacological or genetic inhibition of RHAMM in vitro and in vivo ablates tumor invasiveness and metastatic spread, implicating RHAMM as a potential therapeutic target to restrict tumor growth and improve patient survival. However, RHAMM’s pro-tumor activity is dependent on its subcellular distribution, which complicates the design of RHAMM-directed therapies. An alternative approach is to identify downstream signaling pathways that mediate RHAMM-promoted tumor aggressiveness. Herein, we discuss the pro-tumoral roles of RHAMM and elucidate the corresponding regulators and signaling pathways mediating RHAMM downstream events, with a specific focus on strategies to target the RHAMM signaling network in cancer cells.