MSR1 repeats modulate gene expression and affect risk of breast and prostate cancer

Role of ICAM1 in tumor immunity and prognosis of triple-negative breast cancer

Background

Treating triple-negative breast cancer (TNBC) is a difficult landscape owing to its short survival times and high risk of metastasis and recurrence among patients. Although involved in tumor invasion and metastasis, the mechanism of action of intercellular adhesion molecule 1 (ICAM1), a trans-membrane glycoprotein, in TNBC is ambiguous.

Methods

We examined ICAM1's role in TNBC, focusing on its expression, cell survival, mutation, and tumor immunity. Then, a risk score model was created utilizing co-expressed genes associated with ICAM1. According to their respective risk scores, we divided patients into high- and low-risk groups. Immune function, drug susceptibility differences, and somatic variants were analyzed in the high-and low-risk groups. And we used the CMap database to predict potential medications. Then, TNBC cells with low expression of ICAM-1 were co-cultured with PMA-treated THP-1 cells and CD8 T cells. In addition, We detected the expression of PD-1 and CTLA4 of low ICAM-1 expressing TNBC cells when they were cocultured with CD8 T cells.

Results

ICAM1 was found to be involved in leukocyte cell adhesion, motility, and immune activation. Patients with low-ICAM1 group had shorter disease-free survival (DFS) than those with high-ICAM1 group. The group with elevated levels of ICAM1 exhibited significantly increased levels of T-cell regulation, quiescence in natural killer (NK) cells, and M1 macrophage. ICAM1 expression was correlated with immune checkpoint drugs. The prognostic ability of the risk score model was found to be superior to that of individual genes. Patients categorized as high-risk exhibited elevated clinical stages, showed higher M1 macrophage numbers, and were able to benefit better from immunotherapy. Individuals belonging to the high-risk group exhibit significantly elevated mutation rates in TP53, TTN, and SYNE1 genes, along with increased TMB and PD-L1 levels and decreased TIDE scores. These findings suggest that immunotherapy may be advantageous for the high-risk group. Furthermore, low expression of ICAM1 was found to promote polarization to M2 macrophages along with T-cell exhaustion.

Conclusion

In conclusion, Low ICAM1 expression may be related to immune escape, leading to poor treatment response and a worse prognosis.

Variable number tandem repeats (VNTRs) as modifiers of breast cancer risk in carriers of BRCA1 185delAG

Despite substantial efforts in identifying both rare and common variants affecting disease risk, in the majority of diseases, a large proportion of unexplained genetic risk remains. We propose that variable number tandem repeats (VNTRs) may explain a proportion of the missing genetic risk. Herein, in a pilot study with a retrospective cohort design, we tested whether VNTRs are causal modifiers of breast cancer risk in 347 female carriers of the BRCA1 185delAG pathogenic variant, an important group given their high risk of developing breast cancer. We performed targeted-capture to sequence VNTRs, called genotypes with adVNTR, tested the association of VNTRs and breast cancer risk using Cox regression models, and estimated the effect size using a retrospective likelihood approach. Of 303 VNTRs that passed quality control checks, 4 VNTRs were significantly associated with risk to develop breast cancer at false discovery rate [FDR] < 0.05 and an additional 4 VNTRs had FDR < 0.25. After determining the specific risk alleles, there was a significantly earlier age at diagnosis of breast cancer in carriers of the risk alleles compared to those without the risk alleles for seven of eight VNTRs. One example is a VNTR in exon 2 of LINC01973 with a per-allele hazard ratio of 1.58 (1.07-2.33) and 5.28 (2.79-9.99) for the homozygous risk-allele genotype. Results from this first systematic study of VNTRs demonstrate that VNTRs may explain a proportion of the unexplained genetic risk for breast cancer.

The Pharmacological Mechanism of Curcumin against Drug Resistance in Non-Small Cell Lung Cancer: Findings of Network Pharmacology and Bioinformatics Analysis

The pharmacological mechanism of curcumin against drug resistance in non-small cell lung cancer (NSCLC) remains unclear. This study aims to summarize the genes and pathways associated with curcumin action as an adjuvant therapy in NSCLC using network pharmacology, drug-likeness, pharmacokinetics, functional enrichment, protein-protein interaction (PPI) analysis, and molecular docking. Prognostic genes were identified from the curcumin-NSCLC intersection gene set for the following drug sensitivity analysis. Immunotherapy, chemotherapy, and targeted therapy sensitivity analyses were performed using external cohorts (GSE126044 and IMvigor210) and the CellMiner database. 94 curcumin-lung adenocarcinoma (LUAD) hub targets and 41 curcumin-lung squamous cell carcinoma (LUSC) hub targets were identified as prognostic genes. The anticancer effect of curcumin was observed in KEGG pathways involved with lung cancer, cancer therapy, and other cancers. Among the prognostic curcumin-NSCLC intersection genes, 20 LUAD and 8 LUSC genes were correlated with immunotherapy sensitivity in the GSE126044 NSCLC cohort; 30 LUAD and 13 LUSC genes were associated with immunotherapy sensitivity in the IMvigor210 cohort; and 12 LUAD and 13 LUSC genes were related to chemosensitivity in the CellMiner database. Moreover, 3 LUAD and 5 LUSC genes were involved in the response to targeted therapy in the CellMiner database. Curcumin regulates drug sensitivity in NSCLC by interacting with cell cycle, NF-kappa B, MAPK, Th17 cell differentiation signaling pathways, etc. Curcumin in combination with immunotherapy, chemotherapy, or targeted drugs has the potential to be effective for drug-resistant NSCLC. The findings of our study reveal the relevant key signaling pathways and targets of curcumin as an adjuvant therapy in the treatment of NSCLC, thus providing pharmacological evidence for further experimental research.

Comprehensive analysis of the prognostic and role in immune cell infiltration of MSR1 expression in lower-grade gliomas

BACKGROUND

The therapeutic effects of conventional treatment on gliomas are not promising. The tumor microenvironment (TME) has a close association with the invasiveness of multiple types of tumors, including low-grade gliomas (LGG). This study aims to validate the prognostic and immune-related role of macrophage scavenger receptor 1 (MSR1) in LGG patients.

METHODS

Data in this study were obtained from public databases. The differential expression of MSR1 was analyzed in LGG patients with different clinicopathological characteristics. Kaplan-Meier survival analysis, a time-dependent receiver operating characteristic (ROC) curve, and Cox regression analysis were used to assess the prognostic value of MSR1. Differentially expressed genes (DEGs) were screened between the high and low expression groups of MSR1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to annotate the function of these DEGs. Hallmark gene sets were identified based on MSR1 by Gene Set Enrichment Analysis (GSEA). Difference analysis and correlation analysis were used to study the relationship between MSR1 and TME-related scores, tumor-infiltrating immune cells (TIICs), immune-related gene sets, and immune checkpoints (ICPs). The single-cell sequencing data were processed to identify the cell types expressing MSR1. The quantification of TIICs in TME was calculated by single-sample gene set enrichment analysis (ssGSEA). The differential expression of MSR1 in LGG and control brain tissues was verified by experiments.

RESULTS

There were significant differences in the expression level of MSR1 in different types of tissues and cells. MSR1 has a high prognostic value in LGG patients and can be used as an independent prognostic factor. MSR1 is closely related to TME and may play an important role in the immunotherapy of LGG patients.

CONCLUSIONS

The result of our study demonstrated that MSR1 is an independent prognostic biomarker in LGG patients and may play an important role in the TME of LGGs.

The promising role of new molecular biomarkers in prostate cancer: from coding and non-coding genes to artificial intelligence approaches

Background

Risk stratification or progression in prostate cancer is performed with the support of clinical-pathological data such as the sum of the Gleason score and serum levels PSA. For several decades, methods aimed at the early detection of prostate cancer have included the determination of PSA serum levels. The aim of this systematic review is to provide an overview about recent advances in the discovery of new molecular biomarkers through transcriptomics, genomics and artificial intelligence that are expected to improve clinical management of the prostate cancer patient.

Methods

An exhaustive search was conducted by Pubmed, Google Scholar and Connected Papers using keywords relating to the genetics, genomics and artificial intelligence in prostate cancer, it includes “biomarkers”, “non-coding RNAs”, “lncRNAs”, “microRNAs”, “repetitive sequence”, “prognosis”, “prediction”, “whole-genome sequencing”, “RNA-Seq”, “transcriptome”, “machine learning”, and “deep learning”.

Results

New advances, including the search for changes in novel biomarkers such as mRNAs, microRNAs, lncRNAs, and repetitive sequences, are expected to contribute to an earlier and accurate diagnosis for each patient in the context of precision medicine, thus improving the prognosis and quality of life of patients. We analyze several aspects that are relevant for prostate cancer including its new molecular markers associated with diagnosis, prognosis, and prediction to therapy and how bioinformatic approaches such as machine learning and deep learning can contribute to clinic. Furthermore, we also include current techniques that will allow an earlier diagnosis, such as Spatial Transcriptomics, Exome Sequencing, and Whole-Genome Sequencing.

Conclusion

Transcriptomic and genomic analysis have contributed to generate knowledge in the field of prostate carcinogenesis, new information about coding and non-coding genes as biomarkers has emerged. Synergies created by the implementation of artificial intelligence to analyze and understand sequencing data have allowed the development of clinical strategies that facilitate decision-making and improve personalized management in prostate cancer.

Mechanistic insights into genetic susceptibility to prostate cancer

Prostate cancer (PCa) is the second most common cancer in men and is a highly heritable disease that affects millions of individuals worldwide. Genome-wide association studies have to date discovered nearly 270 genetic loci harboring hundreds of single nucleotide polymorphisms (SNPs) that are associated with PCa susceptibility. In contrast, the functional characterization of the mechanisms underlying PCa risk association is still growing. Given that PCa risk-associated SNPs are highly enriched in noncoding cis-regulatory genomic regions, accumulating evidence suggests a widespread modulation of transcription factor chromatin binding and allelic enhancer activity by these noncoding SNPs, thereby dysregulating gene expression. Emerging studies have shown that a proportion of noncoding variants can modulate the formation of transcription factor complexes at enhancers and CTCF-mediated 3D genome architecture. Interestingly, DNA methylation-regulated CTCF binding could orchestrate a long-range chromatin interaction between PCa risk enhancer and causative genes. Additionally, one-causal-variant-two-risk genes or multiple-risk-variant-multiple-genes are prevalent in some PCa risk-associated loci. In this review, we will discuss the current understanding of the general principles of SNP-mediated gene regulation, experimental advances, and functional evidence supporting the mechanistic roles of several PCa genetic loci with potential clinical impact on disease prevention and treatment.

Identification of inflammation-related DNA methylation biomarkers in periodontitis patients based on weighted co-expression analysis

Evidence from past research has shown that DNA methylation plays a key role in the pathogenesis of periodontitis, regulating gene expression levels and thereby affecting the occurrence of various diseases. Three sample sets of methylation data and gene expression data were downloaded from Gene Expression Omnibus (GEO) database. A diagnostic classifier is established based on gene expression data and CpG methylation data. Abnormal expression of immune-related pathways and methyltransferase-related genes in patients with periodontitis was detected. A total of 8,029 differentially expressed CpG (DMP) was annotated to the promoter region of 4,940 genes, of which 295 immune genes were significantly enriched. The CpG sites of 23 differentially co-expressed immune gene promoter regions were identified, and 13 CpG were generally hypermethylated in healthy group samples, while some were methylated in most patients. Five CpGs were screened as robust periodontitis biomarkers. The accuracy in the training data set, the two external verification data sets, and in the transcriptome was 95.5%, 80% and 78.3%, and 82.6%, respectively. This study provided new features for the diagnosis of periodontitis, and contributed to the personalized treatment of periodontitis.

Potassium Channel Protein KCNK6 Promotes Breast Cancer Cell Proliferation, Invasion, and Migration

Breast cancer is the most common malignant tumor in women, and its incidence is increasing each year. To effectively treat breast cancer, it is important to identify genes involved in its occurrence and development and to exploit them as potential drug therapy targets. Here, we found that potassium channel subfamily K member 6 (KCNK6) is significantly overexpressed in breast cancer, however, its function in tumors has not been reported. We further verified that KCNK6 expression is upregulated in breast cancer biopsies. Moreover, overexpressed KCNK6 was found to enhance the proliferation, invasion, and migration ability of breast cancer cells. These effects may occur by weakening cell adhesion and reducing cell hardness, thus affecting the malignant phenotype of breast cancer cells. Our study confirmed, for the first time, that increased KCNK6 expression in breast cancer cells may promote their proliferation, invasion, and migration. Moreover, considering that ion channels serve as therapeutic targets for many small molecular drugs in clinical treatment, targeting KCNK6 may represent a novel strategy for breast cancer therapies. Hence, the results of this study provide a theoretical basis for KCNK6 to become a potential molecular target for breast cancer treatment in the future.

Bioinformatics analysis reveals that ANXA1 and SPINK5 are novel tumor suppressor genes in patients with oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a solid tumor of squamous epithelial origin. Currently, surgery is still the main treatment for OSCC, with radiotherapy and chemotherapy as important adjuvant treatments. However, the problem of poor prognosis of OSCC patients still exists in clinical practice. To explore further potential biomarkers or treatment targets in OSCC patients, this study used a high-throughput gene expression database to study the potential molecular mechanisms of OSCC carcinogenesis.

METHODS

The GEO database related to OSCC was searched and analyzed using GEO2R. Oncomine and the Human Protein Atlas were used to evaluate the expression level of differentially-expressed genes (DEGs). The cBioPortal dataset was used to analyze the mutations of the potential DEGs and patient survival.

RESULTS

Three GEO datasets, GSE146483, GSE138206, and GSE148944, were downloaded and 7 DEGs were found in common in OSCC tissues. Using Oncomine and the Human Protein Atlas, ANXA1, IL1RN, and SPINK5 were decreased in cancer tissues, while protein levels of APOE and IFI35 were increased accordingly. Interestingly, low levels of ANXA1 and SPINKS were associated with the TNM stage of OSCC patients. No mutations in DEGs were found in OSCC patients, based on the cBioPortal dataset. Survival analysis indicated OSCC patients with high MSR1 had poor overall survival (OS), while low expression of CXCR4, ANXA1, IL1RN, and SPINK5 also predicted poor OS in OSCC patients.

CONCLUSIONS

Our findings uncovered 7 potential biomarkers of OSCC patients, with ANXA1 and SPINK5 serving as potential tumor suppressor genes in OSCC.

Identification of Immune-Related Genes MSR1 and TLR7 in Relation to Macrophage and Type-2 T-Helper Cells in Osteosarcoma Tumor Micro-Environments as Anti-metastasis Signatures

Metastasis of osteosarcoma (OS) is an essential factor affecting the prognosis and survival of patients. The tumor microenvironment, including tumor immune-infiltrating cells (TIIC), is closely related to tumor progression. The purpose of this study was to investigate the differences between metastatic and non-metastatic immune-infiltrating cells in OS and to identify key immune-related genes. The differences in immune infiltration in OS metastasis were calculated based on the ssGSEA algorithm of 28 immuno-infiltrating cells. Weighted gene co-expression network analysis (WGCNA) and intersection analysis were used to screen immune-related modules and hubgenes. Univariate/multivariate/Lasso Cox regressions were used for models construction and signatures screening. The receiver operating characteristic (ROC) and Kaplan-Meier (K-M) curves were constructed to observe the metastases of different groups. Both internal and external data were verified. We found that macrophages and Type-2 T-helper cells were significantly decreased in patients with OS metastases. The high-risk groups obtained from multivariate/Lasso Cox models constructed with 11 immune-related hubgenes almost all underwent distant metastases within 5 years. Interestingly and importantly, two genes, MSR1 and TLR7, appeared in various models and various hubgenes, which play an anti-metastasis role and may prolong overall survival in OS. Our study may help elucidate the impact of TIIC on OS metastasis outcomes and to identify biomarkers and therapeutic targets.

Tribbles-1 Expression and Its Function to Control Inflammatory Cytokines, Including Interleukin-8 Levels are Regulated by miRNAs in Macrophages and Prostate Cancer Cells

The pseudokinase TRIB1 controls cell function in a range of contexts, by regulating MAP kinase activation and mediating protein degradation via the COP1 ubiquitin ligase. TRIB1 regulates polarization of macrophages and dysregulated Trib1 expression in murine models has been shown to alter atherosclerosis burden and adipose homeostasis. Recently, TRIB1 has also been implicated in the pathogenesis of prostate cancer, where it is often overexpressed, even in the absence of genetic amplification. Well described TRIB1 effectors include MAP kinases and C/EBP transcription factors, both in immune cells and in carcinogenesis. However, the mechanisms that regulate TRIB1 itself remain elusive. Here, we show that the long and conserved 3’untranslated region (3’UTR) of TRIB1 is targeted by miRNAs in macrophage and prostate cancer models. By using a systematic in silico analysis, we identified multiple “high confidence” miRNAs potentially binding to the 3’UTR of TRIB1 and report that miR-101-3p and miR-132-3p are direct regulators of TRIB1 expression and function. Binding of miR-101-3p and miR-132-3p to the 3’UTR of TRIB1 mRNA leads to an increased transcription and secretion of interleukin-8. Our data demonstrate that modulation of TRIB1 by miRNAs alters the inflammatory profile of both human macrophages and prostate cancer cells.

The molecular function of kallikrein-related peptidase 14 demonstrates a key modulatory role in advanced prostate cancer

Kallikrein-related peptidase 14 (KLK14) is one of the several secreted KLK serine proteases involved in prostate cancer (PCa) pathogenesis. While relatively understudied, recent reports have identified KLK14 as overexpressed during PCa development. However, the modulation of KLK14 expression during PCa progression and the molecular and biological functions of this protease in the prostate tumor microenvironment remain unknown. To determine the modulation of KLK14 expression during PCa progression, we analyzed the expression levels of KLK14 in patient samples using publicly available databases and immunohistochemistry. In order to delineate the molecular mechanisms involving KLK14 in PCa progression, we integrated proteomic, transcriptomic, and in vitro assays with the goal to identify substrates, related-signaling pathways, and functional roles of this protease. We showed that KLK14 expression is elevated in advanced PCa, and particularly in metastasis. Additionally, KLK14 levels were found to be decreased in PCa tissues from patients responsive to neoadjuvant therapy compared to untreated patients. Furthermore, we also identified that KLK14 expression reoccurred in patients who developed castrate-resistant PCa. The combination of proteomic and transcriptomic analysis as well as functional assays revealed several new KLK14 substrates (agrin, desmoglein 2, vitronectin, laminins) and KLK14-regulated genes (Interleukin 32, midkine, SRY-Box 9), particularly an involvement of the mitogen-activated protein kinase 1 and interleukin 1 receptor pathways, and an involvement of KLK14 in the regulation of cellular migration, supporting its involvement in aggressive features of PCa progression. In conclusion, our work showed that KLK14 expression is associated with the development of aggressive PCa suggesting that targeting this protease could offer a novel route to limit the progression of prostate tumors. Additional work is necessary to determine the benefits and implications of targeting/cotargeting KLK14 in PCa as well as to determine the potential use of KLK14 expression as a predictor of PCa aggressiveness or response to treatment.

A novel mutation in the PRPF31 in a North Indian adRP family with incomplete penetrance

PURPOSE

To identify the underlying genetic defect for non-syndromic autosomal dominant retinitis pigmentosa (adRP) with incomplete penetrance in a North Indian family.

METHODS

Family history and clinical data were collected. Linkage analysis using 72 fluorescently labeled microsatellite markers flanking all the 26 candidate genes known for adRP was performed. Mutation screening in candidate gene at the mapped region was performed by bi-directional DNA sequencing.

RESULTS

Positive two-point lod scores > 1.0 (θ = 0.000) suggestive of linkage were obtained with markers D19S572, D19S927 and D19S926 at 19q13.42, in the vicinity of PRPF31 gene. Mutation screening in all the 14 exonic regions and intron-exon boundaries of PRPF31 revealed a novel change, i.e. c.896G>A (p.Cys299Tyr) in exon eight. The observed change segregated in heterozygous form in all the six affected members and in three carriers, consistent with incomplete penetrance. This substitution was not observed in tested 15 unaffected members and in 200 ethnically matched controls.

CONCLUSION

Present study describes mapping of a locus for non-syndromic adRP with incomplete penetrance at 19q13.42 in a North Indian family and identifies a novel missense mutation (p.Cys299Tyr) in PRPF31 localized at the mapped interval. The observed substitution lies in the NOP domain of PRPF31 that exhibit RNA and protein binding surfaces and thus may interfere in the formation of spliceosome complex. Due to p.Cys299Tyr substitution hydrogen bonds are generated, which may result in conformational changes and PRPF31 protein deformity. Present findings further substantiate the role of PRPF31 in adRP with incomplete penetrance and expand the mutation spectrum of PRPF31.

Aberrant upregulation of KLK10 promotes metastasis via enhancement of EMT and FAK/SRC/ERK axis in PDAC

Pancreatic Ductal Adenocarcinoma (PADC) metastasis is the leading cause of morality of this severe malignant tumor. Proteases are key players in the degradation of extracellular matrix which promotes the cascade of tumor metastasis. As a kind of serine proteases, the kallikrein family performs vital function on the cancer proteolysis scene, which have been proved in diverse malignant tumors. However, the specific member of kallikrein family and its function in PDAC remain unexplored. In this study, by data mining of GEO datasets, we have identified KLK10 is upregulated gene in PDAC. We found that KLK10 was significantly overexpressed in tissues of pancreatic intraepithelial neoplasia (PanIN) and PDAC from Pdx1-Cre; LSL-KrasG12D/+ mice (KC) and Pdx1-Cre; LSL-KrasG12D/+; LSL-Trp53R172H/+ mice (KPC) by immunohistochemical analysis. Moreover, KLK10 is extremely elevated in the PDAC tissues, especially that from the PDAC patients with lymphatic and distant metastasis. Aberrant KLK10 expression is significantly correlated with poor prognosis and shorter survival by univariable and multivariable analysis. Functionally, knockdown of KLK10 observably inhibits invasion and metastatic phenotype of PDAC cells in vitro and metastasis in vivo. In addition, blockade of KLK10 attenuates epithelial-mesenchymal transition and activation of FAK-SRC-ERK signaling, which explains the mechanism of KLK10 in promoting metastasis. Collectively, KLK10 should be considered as a promising biomarker for diagnosis and potential target for therapy in PDAC.