SNP mutation-related genes in breast cancer for monitoring and prognosis of patients: A study based on the TCGA database

Rapid one-pot human single nucleotide polymorphism genotyping platform with Cas13a nuclease

Single nucleotide polymorphism (SNP), as one of the key components of the genetic factors, is important for disease detection and early screening of hereditary diseases. Current SNP genotyping methods require laboratory instruments or long operating times. To facilitate the diagnosis of hereditary diseases, we developed a new method referred to as the LwaCas13a-based SNP genotyping platform (Cas13a platform), which is useful for detecting disease-related SNPs. We report a CRISPR/Cas13a-based SNP genotyping platform that couples recombinase-aided amplification (RAA), T7 transcription, and Leptotrichia wadei Cas13a (LwaCas13a) detection for simple and fast genotyping of human disease-related SNPs. We used this Cas13a platform to identify 17 disease-related SNPs, demonstrating that position 2 in gRNA is suitable for the introduction of additional mismatches to achieve high discrimination in genotyping across a wide range of SNP targets. The discrimination specificity of 17 SNPs was improved 3.0-35.1-fold after introducing additional mismatches at position 2 from the 5'-end. We developed a method, which has a lower risk of cross-contamination and operational complexity, for genotyping SNPs using human saliva samples in an one-pot testing that delivers results within 60 min. Compared to TaqMan probe qPCR, RFLP, AS-PCR and other SNP genotyping methods, the Cas13a platform is simple, rapid and reliable, expanding the applications of the CRISPR/Cas system in nucleic acid detection and SNP genotyping.

Comprehensive review of drug-mediated ICD inhibition of breast cancer: mechanism, status, and prospects

The escalating incidence of breast cancer (BC) in women underscores its grave health threat. Current molecular insights into BC's post-adjuvant therapy cure remain elusive, necessitating active treatment explorations. Immunotherapy, notably chemotherapy-induced immunogenic cell death (ICD), has emerged as a promising BC therapy. ICD harnesses chemotherapeutics to activate anti-tumor immunity via DAMPs, fostering long-term T-cell memory and primary BC cure. Besides chemotherapy drugs, Nanodrugs, traditional Chinese medicine (TCM) and ICIs also induce ICD, boosting immune response. ICIs, like PD-1/PD-L1 inhibitors, revolutionize cancer treatment but face limited success in cold tumors. Thus, ICD induction combined with ICIs is studied extensively for BC immunotherapy. This article reviews the mechanism of ICD related drugs in BC and provides reference for the research and development of BC treatment, in order to explore more effective clinical treatment of BC, we hope to explore more ICD inducers and make ICIs more effective vaccines.

A colorimetric reverse-transcription loop-mediated isothermal amplification method targeting the L452R mutation to detect the Delta variant of SARS-CoV-2

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered global difficulties for both individuals and economies, with new variants continuing to emerge. The Delta variant of SARS-CoV-2 remains most prevalent worldwide, and it affects the efficacy of coronavirus disease 2019 (COVID-19) vaccination. Expedited testing to detect the Delta variant of SARS-CoV-2 and monitor viral transmission is necessary. This study aimed to develop and evaluate a colorimetric reverse-transcription loop-mediated isothermal amplification (RT-LAMP) technique targeting the L452R mutation in the S gene for the specific detection of the Delta variant. In the test, positivity was indicated as a color change from purple to yellow. The assay's 95% limit of detection was 57 copies per reaction for the L452R (U1355G)-specific standard plasmid. Using 126 clinical samples, our assay displayed 100% specificity, 97.06% sensitivity, and 98.41% accuracy in identifying the Delta variant of SARS-CoV-2 compared to real-time RT-PCR. To our knowledge, this is the first colorimetric RT-LAMP assay that can differentiate the Delta variant from its generic SARS-CoV-2, enabling it as an approach for studying COVID-19 demography and facilitating proper effective control measure establishment to fight against the reemerging variants of SARS-CoV-2 in the future.

Mutation-Selected Amplification droplet digital PCR: A new single nucleotide variant detection assay for TP53R249S mutant in tumor and plasma samples

The early detection of gene mutations in physiological and pathological processes is a powerful approach to guide decisions in precision medicine. However, detecting low-copy mutant DNA from clinical samples poses a challenge due to the enrichment of wild-type DNA backgrounds. In this study, we devised a novel strategy, named Mutation-Selected Amplification droplet digital PCR (MSA-ddPCR), to quantitatively analyze single nucleotide variants (SNVs) at low variant allele frequencies (VAFs). Using TP53R249S (a hotspot mutation associated with hepatocellular carcinoma) as a model, we optimized the concentration ratio of primers, the annealing temperature and nucleic acid amplification modifiers. Subsequently, we evaluated the linear range and precision of MSA-ddPCR by detecting TP53R249S and TP53wild-type (TP53WT) plasmid DNA, respectively. MSA-ddPCR demonstrated superior ability to discriminate between mutant DNA and wild-type DNA compared to traditional TaqMan-MGB PCR. We further applied MSA-ddPCR to analyze the TP53R249S mutation in 20 plasma samples and 15 formalin-fixed paraffin-embedded (FFPE) tissue samples, and assessed the agreement rates between MSA-ddPCR and amplicon high-throughput sequencing. The results showed that the limit of blanks of MSA-ddPCR are 0.449 copies μL-1 in the FAM channel and 0.452 copies μL-1 in the VIC channel. MSA-ddPCR could accurately quantify VAFs as low as 0.01 %, surpassing existing PCR and next-generation sequencing (NGS) methods. In the detection of clinical samples, a high correlation was found between MSA-ddPCR and amplicon high-throughput sequencing. Additionally, MSA-ddPCR outperformed sequencing methods in terms of detection time and simplicity of data analysis. MSA-ddPCR can be easily implemented into clinical practice and serve as a robust tool for detecting mutant genes due to its high sensitivity and accuracy.

Oestrogen receptor positive breast cancer and its embedded mechanism: breast cancer resistance to conventional drugs and related therapies, a review

Traditional medication and alternative therapies have long been used to treat breast cancer. One of the main problems with current treatments is that there is an increase in drug resistance in the cancer cells owing to genetic differences such as mutational changes, epigenetic changes and miRNA (microRNA) alterations such as miR-1246, miR-298, miR-27b and miR-33a, along with epigenetic modifications, such as Histone3 acetylation and CCCTC-Binding Factor (CTCF) hypermethylation for drug resistance in breast cancer cell lines. Certain forms of conventional drug resistance have been linked to genetic changes in genes such as ABCB1, AKT, S100A8/A9, TAGLN2 and NPM. This review aims to explore the current approaches to counter breast cancer, the action mechanism, along with novel therapeutic methods endowing potential drug resistance. The investigation of novel therapeutic approaches sheds light on the phenomenon of drug resistance including genetic variations that impact distinct forms of oestrogen receptor (ER) cancer, genetic changes, epigenetics-reported resistance and their identification in patients. Long-term effective therapy for breast cancer includes selective oestrogen receptor modulators, selective oestrogen receptor degraders and genetic variations, such as mutations in nuclear genes, epigenetic modifications and miRNA alterations in target proteins. Novel research addressing combinational therapies including maytansine, photodynamic therapy, guajadiol, talazoparib, COX2 inhibitors and miRNA 1246 inhibitors have been developed to improve patient survival rates.

Polymorphism rs2327430 in TCF21 predicts the risk and prognosis of gastric cancer by affecting the binding between TFAP2A and TCF21

BACKGROUND

Single nuclear polymorphisms (SNPs) have been published to be correlated with multiple diseases. Transcription Factor 21 (TCF21) is a critical transcription factor involved in various types of cancers. However, the association of TCF21 genetic polymorphisms with gastric cancer (GC) susceptibility and prognosis remains unclear.

METHODS

A case-control study comprising 890 patients diagnosed with GC and an equal number of cancer-free controls was conducted. After rigorous statistical analysis, molecular experiments were carried out to elucidate the functional significance of the SNPs in the context of GC.

RESULTS

TCF21 rs2327430 (OR = 0.78, P = 0.026) provides protection against GC, while rs4896011 (OR = 1.39, P = 0.005) exhibit significant associations with GC risk. Furthermore, patients with the (TC + CC) genotype of rs2327430 demonstrate a relatively favorable prognosis (OR = 0.47, P = 0.012). Mechanistically, chromatin immunoprecipitation assay and luciferase reporter assay revealed that the C allele of rs2327430 disrupts the binding of Transcription Factor AP-2 Alpha (TFAP2A) to the promoter region of TCF21, resulting in increased expression of TCF21 and inhibition of malignant behaviors in GC cells.

CONCLUSION

Our findings highlight the significant role of TCF21 SNPs in both the risk and prognosis of GC and provide valuable insights into the underlying molecular mechanisms. Specifically, the disruptive effect of rs2327430 on TCF21 expression and its ability to modulate malignant cell behaviors suggest that rs2327430 may serve as a potential predictive marker for GC risk and prognosis.

Association Between Polymorphisms in DNA Damage Repair Pathway Genes and Female Breast Cancer Risk

Breast cancer risk have been discussed to be associated with polymorphisms in genes as well as abnormal DNA damage repair function. This study aims to assess the relationship between genes single nucleotide polymorphisms (SNPs) related to DNA damage repair and female breast cancer risk in Chinese population. A case-control study containing 400 patients and 400 healthy controls was conducted. Genotype was identified using the sequence MassARRAY method and expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2) in tumor tissues was analyzed by immunohistochemistry assay. The results revealed that ATR rs13091637 decreased breast cancer risk influenced by ER, PR (CT/TT vs. CC: adjusted odds ratio [OR] = 1.54, 95% confidence interval [CI]: 1.04-2.27, p = 0.032; CT/TT vs. CC: adjusted OR = 1.63, 95%CI: 1.14-2.35, p = 0.008) expression. Stratified analysis revealed that PALB2 rs16940342 increased breast cancer risk in response to menstrual status (AG/GG vs. AA: adjusted OR = 1.72, 95%CI: 1.13-2.62, p = 0.011) and age of menarche (AG/GG vs. AA: adjusted OR = 1.54, 95%CI: 1.03-2.31, p = 0.037), whereas ATM rs611646 and Ku70 rs132793 were associated with reduced breast cancer risk influenced by menarche (GA/AA vs. GG: adjusted OR = 0.50, 95%CI: 0.30-0.95, p = 0.033). In a summary, PALB2 rs16940342, ATR rs13091637, ATM rs611646, and Ku70 rs132793 were associated with breast cancer risk.

Impact of NDUFAF6 on breast cancer prognosis: linking mitochondrial regulation to immune response and PD-L1 expression

BACKGROUND

Breast cancer is a major global health concern, and there is a continuous search for novel biomarkers to predict its prognosis. The mitochondrial protein NDUFAF6, previously studied in liver cancer, is now being investigated for its role in breast cancer. This study aims to explore the expression and functional significance of NDUFAF6 in breast cancer using various databases and experimental models.

METHODS

We analyzed breast cancer samples from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA) databases, supplemented with immunohistochemistry (IHC) staining to assess NDUFAF6 expression. A breast cancer cell xenograft mouse model was used to evaluate tumor growth, apoptosis, and NDUFAF6 expression. Survival probabilities were estimated through Kaplan-Meier plots and Cox regression analysis. A Protein-Protein Interaction (PPI) network was constructed, and differentially expressed genes related to NDUFAF6 were analyzed using GO, KEGG, and GSEA. The relationship between NDUFAF6 expression, immune checkpoints, and immune infiltration was also evaluated.

RESULTS

NDUFAF6 was found to be overexpressed in breast cancer patients and in the xenograft mouse model. Its expression correlated with worse clinical features and prognosis. NDUFAF6 expression was an independent predictor of breast cancer outcomes in both univariate and multivariate analyses. Functionally, NDUFAF6 is implicated in several immune-related pathways. Crucially, NDUFAF6 expression correlated with various immune infiltrating cells and checkpoints, particularly promoting PD-L1 expression by inhibiting the NRF2 signaling pathway.

CONCLUSION

The study establishes NDUFAF6 as a potential prognostic biomarker in breast cancer. Its mechanism of action, involving the inhibition of NRF2 to upregulate PD-L1, highlights its significance in the disease's progression and potential as a target for immunotherapy.

Association Between Multiple Single Nucleotide Polymorphisms in Folate Metabolism Pathway and Breast Cancer Risk in Georgian Women: A Case-Control Study

Background

The folate metabolism pathway plays an integral part in DNA synthesis, methylation, and repair. Methylenetetrahydrofolate reductase (MTHFR) and methylenetetrahydrofolate dehydrogenase (MTHFD1) are both enzymes that are involved in this pathway, and the single nucleotide polymorphisms (SNPs) in genes coding for them have modulatory effects on DNA expression. This study aimed to investigate the relationship between MTHFR C677T (rs1801133) and MTHFD1 G1958A (rs2236225) polymorphisms and the risk of developing breast cancer in Georgian women.

Methods

A case-control study was performed examining the MTHFR C677T and MTHFD1 G1958A SNP in breast cancer-confirmed cases and healthy matched controls. Real time-polymerase chain reaction (PCR) was used to genotype SNPs. The case individuals' pathology reports were obtained following surgeries for cancer characteristic data. Statistical analysis was performed to investigate the significance of the acquired data.

Results

Statistical analysis of MTHFR C677T SNP revealed that the CT genotype increased the risk of breast cancer by 2.17 folds in the over-dominant model. Statistical analysis of MTHFD1 G1958A SNP showed that the GA genotype increased the risk of breast cancer by 4.12 folds in the codominant model and 2.41 folds in the over-dominant model. No statistically significant link was found between genotypes and lymph node status, however, patients with the CT genotype had higher percentages of proliferative activity.

Conclusions

Breast cancer seems to have a statistically significant association with the CT genotype in MTHFR C677T and the GA genotype in MTHFD1 G1958A in Georgian women.

Identification of somatic mutation-driven enhancers and their clinical utility in breast cancer

Somatic mutations contribute to cancer development by altering the activity of enhancers. In the study, a total of 135 mutation-driven enhancers, which displayed significant chromatin accessibility changes, were identified as candidate risk factors for breast cancer (BRCA). Furthermore, we identified four mutation-driven enhancers as independent prognostic factors for BRCA subtypes. In Her2 subtype, enhancer G > C mutation was associated with poorer prognosis through influencing its potential target genes FBXW9, TRIR, and WDR83. We identified aminoglutethimide and quinpirole as candidate drugs targeting the mutated enhancer. In normal subtype, enhancer G > A mutation was associated with poorer prognosis through influencing its target genes ALOX15B, LINC00324, and MPDU1. We identified eight candidate drugs such as erastin, colforsin, and STOCK1N-35874 targeting the mutated enhancer. Our findings suggest that somatic mutations contribute to breast cancer subtype progression by altering enhancer activity, which could be potential candidates for cancer therapy.

Somatic mutations in a multigene panel and impact on prognosis based on TP53 status in Chinese HER2-positive patients undergoing neoadjuvant therapy: A single-institution retrospective cohort

BACKGROUND

Gene mutations play a crucial role in the occurrence and development of tumors, particularly in breast cancer (BC). Neoadjuvant therapy (NAT) has shown greater clinical benefit in HER2-positive breast cancer. However, further clinical investigation is needed to fully understand the correlation between genetic mutations and NAT efficacy and the long-term prognosis in HER2-positive BC.

METHODS

This was a retrospective cohort study of 222 patients receiving NAT between 2017 and 2021 in the Department of Breast Surgery of Fudan University Shanghai Cancer Center. Tumor samples from these patients were subjected to Next Generation Sequencing (NGS) to analyze mutations in 513 cancer-related genes. This study aimed to investigate the association between these genetic mutations and postoperative pathological complete response (pCR), as well as their impact on disease-free survival (DFS).

RESULTS

In total, 48.65% patients reached pCR, ER-negative status (p < 0.001), PR-negative status (p < 0.001), Ki67 ≥ 20 (p = 0.011), and dual-targeted therapy (p < 0.001) were all associated with enhanced pCR rates. The frequency of somatic alterations in TP53 (60%), PIK3CA (15%), and ERBB2 (11%) was highest. In the HER2+/HR- cohort, patients who achieved pCR had a significant benefit in prognosis (HR = 3.049, p = 0.0498). KMT2C (p = 0.036) and TP53 (p = 0.037) mutations were significantly increased in patients with DFS events. Moreover, TP53 mutations had prognostic significance in HER2-positive BC patients with HR-negative (HR = 3.712, p = 0.027) and pCR (HR = 6.253, p = 0.027) status and who received herceptin-only targeted therapy (HR = 4.145, p = 0.011).

CONCLUSIONS

The genetic mutation profiles of Chinese HER2+ patients who received NAT were discrepant with respect to HR status or DFS events. TP53 mutations have significant prognostic value in patients with NAT for HER2-positive BC and patients benefit differently depending on HR status, the neoadjuvant regimen and response, which highlights the significance of genetic factors in treatment customization based on individual genetic and clinical characteristics.

CYP4B1 polymorphisms and the risk of breast cancer in Chinese women: a case-control study

BACKGROUND

Breast cancer (BC) is one of the malignant diseases threatening the life and health of women worldwide. The CYP4B1 gene was abnormally expressed in BC and was associated with the prognosis of BC patients. This study aimed to explore the relationship between CYP4B1 single nucleotide polymorphisms (SNPs) and BC risk in Chinese women.

METHODS

A case-control study of 1,143 women (571 patients and 572 healthy individuals) was conducted. Rs2297813 G/T, rs12142787 G/A, and rs3766197 C/T in CYP4B1 were selected and genotyped by MassARRAY system. The relationships between these SNPs and the risk of BC were assessed by logistic regression analysis. In addition, multi-factor dimensionality reduction (MDR) was used to analyze SNP-SNP interactions.

RESULTS

CYP4B1 rs2297813 had a risk-increasing effect on BC in women with body mass index (BMI) ≤ 24 kg/m2 (OR = 1.72, p = 0.026). CYP4B1 rs12142787 was associated with an increased BC risk in smokers (AA: OR = 1.32, p = 0.045). Among non-drinkers, rs2297813 (OR = 1.69, p = 0.009) and rs12142787 (OR = 1.51, p = 0.020) were related to an increased incidence of BC. CYP4B1 rs3766197 (OR = 1.61p = 0.031) was associated with a higher risk of advanced stages (III/IV stage) of BC. Besides, the contributions of CYP4B1 rs2297813 (OR = 1.55, p = 0.021) and rs12142787 (OR = 1.53, p = 0.033) to BC risk might be associated with more than one birth in patients with BC. The three-locus model consisting of rs2297813, rs12142787, and rs3766197 was regarded as the best predictive model for BC risk.

CONCLUSION

CYP4B1 SNPs were associated with BC risk in Chinese women, especially in patients with BMI ≤ 24 kg/m2, smokers, non-drinkers, patients in advanced stages (III/IV stage), and patients who reproduced once. These findings shed light on the relationship between CYP4B1 SNPs and BC risk in Chinese women.

Delineating highly transcribed noncoding elements landscape in breast cancer

Highly transcribed noncoding elements (HTNEs) are critical noncoding elements with high levels of transcriptional capacity in particular cohorts involved in multiple cellular biological processes. Investigation of HTNEs with persistent aberrant expression in abnormal tissues could be of benefit in exploring their roles in disease occurrence and progression. Breast cancer is a highly heterogeneous disease for which early screening and prognosis are exceedingly crucial. In this study, we developed a HTNE identification framework to systematically investigate HTNE landscapes in breast cancer patients and identified over ten thousand HTNEs. The robustness and rationality of our framework were demonstrated via public datasets. We revealed that HTNEs had significant chromatin characteristics of enhancers and long noncoding RNAs (lncRNAs) and were significantly enriched with RNA-binding proteins as well as targeted by miRNAs. Further, HTNE-associated genes were significantly overexpressed and exhibited strong correlations with breast cancer. Ultimately, we explored the subtype-specific transcriptional processes associated with HTNEs and uncovered the HTNE signatures that could classify breast cancer subtypes based on the properties of hormone receptors. Our results highlight that the identified HTNEs as well as their associated genes play crucial roles in breast cancer progression and correlate with subtype-specific transcriptional processes of breast cancer.

Identification of SNP markers for canine mammary gland tumours in females based on a genome-wide association study - preliminary results

Introduction

The development of genetic research over recent decades has enabled the discovery of new genetic markers, such as single nucleotide polymorphisms (SNPs). This, as well as the full sequencing of the dog genome, has enabled genome-wide association studies (GWAS) to be used in the search for genetic causes of canine mammary tumours (CMTs).

Material and Methods

Genotypic data containing 175,000 SNPs, which had been obtained using the Illumina CanineHD BeadChip microarray technique, were available for analysis in this study. The data concerned 118 bitches, including 36 animals with CMT, representing various breeds and age groups. Statistical analysis was performed in two steps: quality control of genotyping data and genome-wide association analysis based on dominant, recessive, overdominant, codominant, and log-additive models with the single SNP effects.

Results

A total of 40 different SNPs significantly associated with CMT appearance were detected. Moreover, twelve SNPs showed statistical significance in more than one model. Of all the significant SNPs, two, namely BICF2G630136001 in the overdominant model and TIGRP2P107898_rs9044787 in the log-additive model, reached the 5-8 significance level. The other SNPs were significant to a 1-5 level.

Conclusion

In the group of SNPs indicated as significant in the GWAS analysis, several transpired to be localised within genes that may play an important role in CMT.

Evaluating the association of rs6983267 polymorphism of the CCAT2 gene with thyroid cancer susceptibility in the Iranian Azeri population

Thyroid cancer is the most common malignancy of the endocrine system. LncRNAs play critical role in various cellular processes and are associated with several diseases. CCAT2 is a lncRNA molecule overexpressed in thyroid cancer. Single nucleotide polymorphisms in CCAT2 gene can cause changes in the structure and function of CCAT2 transcripts and susceptibility to several diseases. This study aimed to evaluate the association of rs6983267 in CCAT2 gene with thyroid cancer susceptibility in the Azeri population of Iran. In this "case-control" study, genomic DNA was extracted from peripheral blood of 102 individuals affected by thyroid cancer and 103 healthy individuals as controls. Genotyping was performed using TETRA-ARMS polymerase chain reaction. Statistical analysis showed no significant association between genotypes and/or alleles with the occurrence of thyroid cancer in the studied population, patients' gender, and tumor type. Nevertheless, we found that the allelic and genotypic distribution of this SNP was associated with the size of thyroid tumors in patients. It is assumed that investigating more individuals from both case and control group may further determine the genotypic and allelic frequencies of this SNP locus in Iranian-Azeri population.

Subtype Classification, Immune Infiltration, and Prognosis Analysis of Lung Adenocarcinoma Based on Pyroptosis-Related Genes

The effect of pyroptosis-related genes (PRGs) on the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. Thus, this study is aimed at evaluating the prognostic value of PRGs in patients with LUAD and to elucidate their role in the TME and their effect on immunotherapy. Transcriptomic and clinical data were obtained from the Cancer Genome Atlas and the Gene Expression Omnibus databases (GSE3141, GSE31210). Patients with LUAD were classified using consistent clustering, and the differences in the TME for each type were determined using the ESTIMATE and CIBERSORT algorithms. PRGs were screened using univariate regression analysis, and a prognostic risk model was constructed using LASSO regression analysis. The tumor mutational burden and the tumor immune dysfunction and exclusion algorithms were used to predict therapeutic sensitivity in LUAD patients. Then, we evaluated the potential therapeutic interventions using the GDSC database. LUAD patients in cluster 2 had significantly shorter overall survival and progression-free survival rates, lower immune scores, and higher infiltration of T follicular helper cells than those in cluster 1. We used five PRGs to classify patients with LUAD into different risks groups and found that the high-risk group is sensitive to immunotherapy; however, its immune-related pathways were inhibited, which may be related to tumor metabolic reprogramming. Lastly, we identified several potential therapeutic drugs for application in low-risk patients who were less sensitive to immunotherapy. Overall, our findings showed that PRGs can be used to predict prognosis and may aid in the development of personalized therapeutic strategies in LUAD patients.

SDC4-rs1981429 and ATM-rs228590 may provide early biomarkers of breast cancer risk

In Australia, 13% of women are diagnosed with breast cancer (BC) in their lifetime with approximately 20,000 women diagnosed with the disease in 2021. BC is characterised by complex histological and genomic influences with recent advances in cancer biology improving early diagnosis and personalised treatment interventions. The Phosphatidyl-inositol-3-kinase/Protein kinase B (PI3K/AKT) pathway is essential in apoptosis resistance, cell survival, activation of cellular responses to DNA damage and DNA repair. Heparan sulfate proteoglycans (HSPGs) are ubiquitous molecules found on the cell surface and in the extracellular matrix with essential functions in regulating cell survival, growth, adhesion and as mediators of cell differentiation and migration. HSPGs, particularly the syndecans (SDCs), have been linked to cancers, making them an exciting target for anticancer treatments. In the PI3K/AKT pathway, syndecan-4 (SDC4) has been shown to downregulate AKT Serine/Threonine Kinase (AKT1) gene expression, while the ATM Serine/Threonine Kinase (ATM) gene has been found to inhibit this pathway upstream of AKT. We investigated single-nucleotide polymorphisms (SNPs) in HSPG and related genes SDC4, AKT1 and ATM and their influence on the prevalence of BC. SNPs were genotyped in the Australian Caucasian Genomics Research Centre Breast Cancer (GRC-BC) population and in the Griffith University-Cancer Council Queensland Breast Cancer Biobank (GU-CCQ BB) population. We identified that SDC4-rs1981429 and ATM-rs228590 may influence the development and progression of BC, having the potential to become biomarkers in early BC diagnosis and personalised treatment.

Association of GAB2 with Quality of Life and Negative Emotions in Patients with Gastric Cancer after Postoperative Comprehensive Care

GRB2-associated binding protein 2 (GAB2), a highly conserved scaffold protein, is abnormally expressed and activated in patients with gastric cancer (GC). However, the genetic diversity of GAB2 in GC and its association with the clinical manifestations of patients are still unclear. Here, we explored the polymorphism of GAB2 rs2373115 in GC and its association with quality of life (QOL) and negative emotions of patients with GC after postoperative comprehensive care. A case-control study showed that the frequency of the GG genotype of GAB2 rs2373115 in the GC patients was higher than that in the healthy people, while the frequency of the TT + TG genotype was lower than that in the healthy people. Obvious distinctions were observed in the histological grade and TNM staging between the GG genotype and TT + TG genotype. In addition, SAS and SDS scores in the patients with GG genotype were higher than those in patients with TT + TG genotype, while the emotional function, cognitive function, dyspnea, fatigue, sleep disorder, and overall QOL in patients with GG genotype were lower than those in patients with TT + TG genotype. These results showed that GAB2 rs2373115 polymorphism was related to QOL and negative emotions in patients with GC after postoperative comprehensive care.

Competitive SNP-LAMP probes for rapid and robust single-nucleotide polymorphism detection

In this work, we developed a simple and robust assay to rapidly detect SNPs in nucleic acid samples. Our approach combines loop-mediated isothermal amplification (LAMP)-based target amplification with fluorescent probes to detect SNPs with high specificity. A competitive "sink" strand preferentially binds to non-SNP amplicons and shifts the free energy landscape to favor specific activation by SNP products. We demonstrated the broad utility and reliability of our SNP-LAMP method by detecting three distinct SNPs across the human genome. We also designed an assay to rapidly detect highly transmissible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants from crude biological samples. This work demonstrates that competitive SNP-LAMP is a powerful and universal method that could be applied in point-of-care settings to detect any target SNP with high specificity and sensitivity. We additionally developed a publicly available web application for researchers to design SNP-LAMP probes for any target sequence of interest.

A Novel Five-Gene Signature Related to Clinical Outcome and Immune Microenvironment in Breast Cancer

Breast cancer (BC) is the most frequent cancer in women and the main cause of cancer-related deaths in the globe, according to the World Health Organization. The need for biomarkers that can help predict survival or guide treatment decisions in BC patients is critical in order to provide each patient with an individualized treatment plan due to the wide range of prognoses and therapeutic responses. A reliable prognostic model is essential for determining the best course of treatment for patients. Patients’ clinical and pathological data, as well as their mRNA expression levels at level 3, were gleaned from the TCGA databases. Differentially expressed genes (DEGs) between BC and non-tumor specimens were identified. Tumor immunity analyses have been utilized in order to decipher molecular pathways and their relationship to the immune system. The expressions of KIF4A in BC cells were determined by RT-PCR. To evaluate the involvement of KIF4A in BC cell proliferation, CCK-8 tests were used. In this study, utilizing FC > 4 and p < 0.05, we identified 140 upregulated genes and 513 down-regulated genes. A five-gene signature comprising SFRP1, SAA1, RBP4, KIF4A and COL11A1 was developed for the prediction of overall survivals of BC. Overall survival was distinctly worse for patients in the high-risk group than those in the low-risk group. Cancerous and aggressiveness-related pathways and decreased B cell, T cell CD4⁺, T cell CD8⁺, Neutrophil and Myeloid dendritic cells levels were seen in the high-risk group. In addition, we found that KIF4A was highly expressed in BC and its silence resulted in the suppression of the proliferation of BC cells. Taken together, as a possible prognostic factor for BC, the five-gene profile created and verified in this investigation could guide the immunotherapy selection.

Integrated Analysis of lncRNA-Associated ceRNA Network Identifies Two lncRNA Signatures as a Prognostic Biomarker in Gastric Cancer

Background

Gastric cancer (GC) is a malignant tumour that originates in the gastric mucosal epithelium and is associated with high mortality rates worldwide. Long noncoding RNAs (lncRNAs) have been identified to play an important role in the development of various tumours, including GC. Yet, lncRNA biomarkers in a competing endogenous RNA network (ceRNA network) that are used to predict survival prognosis remain lacking. The aim of this study was to construct a ceRNA network and identify the lncRNA signature as prognostic factors for survival prediction.

Methods

The lncRNAs with overall survival significance were used to construct the ceRNA network. Function enrichment, protein-protein interaction, and cluster analysis were performed for dysregulated mRNAs. Multivariate Cox proportional hazards regression was performed to screen the potential prognostic lncRNAs. RT-qPCR was used to measure the relative expression levels of lncRNAs in cell lines. CCK8 assay was used to assess the proliferation of GC cells transfected with sh-lncRNAs.

Results

Differentially expressed genes were identified including 585 lncRNAs, 144 miRNAs, and 2794 mRNAs. The ceRNA network was constructed using 35 DElncRNAs associated with overall survival of GC patients. Functional analysis revealed that these dysregulated mRNAs were enriched in cancer-related pathways, including TGF-beta, Rap 1, calcium, and the cGMP-PKG signalling pathway. A multivariate Cox regression analysis and cumulative risk score suggested that two of those lncRNAs (LINC01644 and LINC01697) had significant prognostic value. Furthermore, the results indicate that LINC01644 and LINC01697 were upregulated in GC cells. Knockdown of LINC01644 or LINC01697 suppressed the proliferation of GC cells.

Conclusions

The authors identified 2-lncRNA signature in ceRNA regulatory network as prognostic biomarkers for the prediction of GC patient survival and revealed that silencing LINC01644 or LINC01697 inhibited the proliferation of GC cells.

B4GALNT2 Gene Promotes Proliferation, and Invasiveness and Migration Abilities of Model Triple Negative Breast Cancer (TNBC) Cells by Interacting With HLA-B Protein

B4GALNT2 gene encodes the enzyme β1,4-N-acetylgalactosaminyltransferase 2 that biosynthesizes the histo-blood group antigen Sda, which is expressed on the surface of erythrocytes and in body secretions. Analysis of The Cancer Genome Atlas (TCGA) database revealed that this gene was highly expressed in breast cancer tissues in comparison with adjacent healthy ones. In-vitro lentivirus-assisted B4GALNT2 gene knockdown experiments in model triple negative breast cancer (TNBC) cell lines (HCC1937 and MDA-MB-231) showed inhibition in cell proliferation, decrease in cell viability, promotion of cell apoptosis and inhibitions in cell migration and invasiveness abilities in comparison with empty lentivirus transfectant controls. Also, in cell cycle tests, the number of cells in the G1 phase increased, in the S phase decreased and did not change in the G2/M phase (indicative of the presence of a block in the G1 phase). In-vivo tumor formation experiments in mice revealed that knockdown of the B4GALNT2 gene in MDA-MB-231 cells inhibited their proliferation. Using co-immunoprecipitation (Co-IP) mass spectroscopy-assisted analysis, it was found that HLA-B protein [a product of the human leukocyte antigen (HLA) class I gene] interacts with B4GALNT2 protein. In-vitro overexpression of HLA-B in B4GALNT2-knocked down MDA-MB-231 cell lines significantly recovered the cell proliferation, viability and migration ability of B4GALNT2 gene. These indicate that HLA-B is one of the interaction proteins in the downstream pathway of the B4GALNT2 gene.

Comprehensive Analysis of the Immune-Oncology Targets and Immune Infiltrates of N 6-Methyladenosine-Related Long Noncoding RNA Regulators in Breast Cancer

Breast cancer (BRCA) has become the highest incidence of cancer due to its heterogeneity. To predict the prognosis of BRCA patients, sensitive biomarkers deserve intensive investigation. Herein, we explored the role of N⁶-methyladenosine-related long non-coding RNAs (m⁶A-related lncRNAs) as prognostic biomarkers in BRCA patients acquired from The Cancer Genome Atlas (TCGA; n = 1,089) dataset and RNA sequencing (RNA-seq) data (n = 196). Pearson’s correlation analysis, and univariate and multivariate Cox regression were performed to select m⁶A-related lncRNAs associated with prognosis. Twelve lncRNAs were identified to construct an m⁶A-related lncRNA prognostic signature (m⁶A-LPS) in TCGA training (n = 545) and validation (n = 544) cohorts. Based on the 12 lncRNAs, risk scores were calculated. Then, patients were classified into low- and high-risk groups according to the median value of risk scores. Distinct immune cell infiltration was observed between the two groups. Patients with low-risk score had higher immune score and upregulated expressions of four immune-oncology targets (CTLA4, PDCD1, CD274, and CD19) than patients with high-risk score. On the contrary, the high-risk group was more correlated with overall gene mutations, Wnt/β-catenin signaling, and JAK-STAT signaling pathways. In addition, the stratification analysis verified the ability of m⁶A-LPS to predict prognosis. Moreover, a nomogram (based on risk score, age, gender, stage, PAM50, T, M, and N stage) was established to evaluate the overall survival (OS) of BRCA patients. Thus, m⁶A-LPS could serve as a sensitive biomarker in predicting the prognosis of BRCA patients and could exert positive influence in personalized immunotherapy.

Transcriptomic heterogeneity of driver gene mutations reveals novel mutual exclusivity and improves exploration of functional associations

Background

Lung adenocarcinoma (LUAD), as the most common subtype of lung cancer, is the leading cause of cancer deaths in the world. The accumulation of driver gene mutations enables cancer cells to gradually acquire growth advantage. Therefore, it is important to understand the functions and interactions of driver gene mutations in cancer progression.

Methods

We obtained gene mutation data and gene expression profile of 506 LUAD tumors from The Cancer Genome Atlas (TCGA). The subtypes of tumors with driver gene mutations were identified by consensus cluster analysis.

Results

We found 21 significantly mutually exclusive pairs consisting of 20 genes among 506 LUAD patients. Because of the increased transcriptomic heterogeneity of mutations, we identified subtypes among tumors with non‐silent mutations in driver genes. There were 494 mutually exclusive pairs found among driver gene mutations within different subtypes. Furthermore, we identified functions of mutually exclusive pairs based on the hypothesis of functional redundancy of mutual exclusivity. These mutually exclusive pairs were significantly enriched in nuclear division and humoral immune response, which played crucial roles in cancer initiation and progression. We also found 79 mutually exclusive triples among subtypes of tumors with driver gene mutations, which were key roles in cell motility and cellular chemical homeostasis. In addition, two mutually exclusive triples and one mutually exclusive triple were associated with the overall survival and disease‐specific survival of LUAD patients, respectively.

Conclusions

We revealed novel mutual exclusivity and generated a comprehensive functional landscape of driver gene mutations, which could offer a new perspective to understand the mechanisms of cancer development and identify potential biomarkers for LUAD therapy.

Use of Electrocatalysis for Differentiating DNA Polymorphisms and Enhancing the Sensitivity of Electrochemical Nucleic Acid-Based Sensors with Covalent Redox Tags-Part II

Single-nucleotide polymorphisms (SNPs), insertion/deletion (indel) polymorphisms, and DNA methylation are the most frequent types of genetic variations. As such, DNA polymorphisms play significant roles in genetic mapping and diagnostics. Thus, analytical methods enabling DNA polymorphism detection will provide an invaluable means for early disease diagnosis. However, no single electrochemical nucleic acid-based sensor has achieved the detection of the three major polymorphisms (SNPs, indel polymorphisms, and DNA methylation) with sufficient specificity and sensitivity. In response, we explore the utilization of a catalytic reaction between methylene blue (MB) covalently linked to surface-bound nucleic acid and freely diffusing ferricyanide (Fe(CN)₆^3-) to improve specificity and sensitivity of DNA polymorphism detection. We find that the dynamics of the nucleic acid tether is an additional rate-limiting factor for the electrocatalytic reaction, in addition to the more traditional kinetic and excess factors. Our proof-of-concept experiments demonstrate that the use of electrocatalysis enables differentiation of the three polymorphisms when target sequences are present at 10 nM. We hypothesize that this ability is a result of the distinct dynamics of the DNA probe with each respective polymorphism. In addition to the specificity the sensor displays, the sensor achieves a 20 pM limit of detection. We believe that the electrocatalysis between nucleic acid-tethered MB and Fe(CN)₆^3- is highly promising for electrochemical nucleic acid-based sensors to achieve better specificity and sensitivity.

Screening and identification of biomarkers associated with the diagnosis and prognosis of lung adenocarcinoma

BACKGROUND

In this study, we aimed to identify the pathogenesis and prognostic biomarkers of lung adenocarcinoma (LUAD).

METHODS

Differentially expressed mRNAs (DEmRNAs) and single nucleotide polymorphism (SNP) mutant genes were screened. In addition, enrichment and protein-protein interaction (PPI) network analyses of the SNP-mutated genes were performed. Thereafter, the correlation between gene mutation and expression was analyzed. Finally, the mutated genes associated with LUAD prognosis were validated on the basis of The Cancer Genome Atlas (TCGA) database.

RESULTS

A total of 2502 DEmRNAs were initially screened in this study. We identified 756 SNP-mutated genes from more than 30 cases. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the mutated genes involved in LUAD were mainly associated with the ECM-receptor interaction, focal adhesion, and calcium signaling pathways. Tumor protein p53 (TP53) and neurexin 1 (NRXN1) with the higher degree were chosen as the hub genes in the PPI network. In addition, the correlation analysis revealed six genes, including assembly factor for spindle microtubules (ASPM), centromere protein F (CENPF), contactin 3 (CNTN3), catenin delta 2 (CTNND2), PKHD1 like 1 (PKHD1L1), and semaphorin 6D (SEMA6D), and three SNP mutations at ASPM rs368020495, CENPF rs762653487, and PKHD1L1 rs768349010 sites that were found to be associated with LUAD prognosis. Further validation showed that among the aforementioned six mutated genes, CENPF was upregulated and SEMA6D was downregulated.

CONCLUSION

CENPF, SEMA6D, TP53, and NRXN1 were found to be closely associated with the development of LUAD.

Detecting Cancer Survival Related Gene Markers Based on Rectified Factor Network

Detecting gene sets that serve as biomarkers for differentiating patient survival groups may help diagnose diseases robustly and develop multi-gene targeted therapies. However, due to the exponential growth of search space imposed by gene combinations, the performance of existing methods is still far from satisfactory. In this study, we developed a new method called BISG (BIclustering based Survival-related Gene sets detection) based on a rectified factor network (RFN) model, which allows efficiently biclustering gene subsets. By correlating genes in each significant bicluster with patient survival outcomes using a log-rank test and multi-sampling strategy, multiple survival-related gene sets can be detected. We applied BISG on three different cancer types, and the resulting gene sets were tested as biomarkers for survival analyses. Secondly, we systematically analyzed 12 different cancer datasets. Our analysis shows that the genes in all the survival-related gene sets are mainly from five gene families: microRNA protein coding host genes, zinc fingers C2H2-type, solute carriers, CD (cluster of differentiation) molecules, and ankyrin repeat domain containing genes. Moreover, we found that they are mainly enriched in heme metabolism, apoptosis, hypoxia and inflammatory response-related pathways. We compared BISG with two other methods, GSAS and IPSOV. Results show that BISG can better differentiate patient survival groups in different datasets. The identified biomarkers suggested by our study provide useful hypotheses for further investigation. BISG is publicly available with open source at https://github.com/LingtaoSu/BISG.

Identification of breast cancer risk modules via an integrated strategy

Breast cancer is one of the most common malignant cancers among females worldwide. This complex disease is not caused by a single gene, but resulted from multi-gene interactions, which could be represented by biological networks. Network modules are composed of genes with significant similarities in terms of expression, function and disease association. Therefore, the identification of disease risk modules could contribute to understanding the molecular mechanisms underlying breast cancer. In this paper, an integrated disease risk module identification strategy was proposed according to a multi-objective programming model for two similarity criteria as well as significance of permutation tests in Markov random field module score, function consistency score and Pearson correlation coefficient difference score. Three breast cancer risk modules were identified from a breast cancer-related interaction network. Genes in these risk modules were confirmed to play critical roles in breast cancer by literature review. These risk modules were enriched in breast cancer-related pathways or functions and could distinguish between breast tumor and normal samples with high accuracy for not only the microarray dataset used for breast cancer risk module identification, but also another two independent datasets. Our integrated strategy could be extended to other complex diseases to identify their risk modules and reveal their pathogenesis.

Abnormally localized DLK1 interacts with NCOR1 in non-small cell lung cancer cell nuclear

Delta-like homolog 1 (DLK1) regulates noncanonical Notch signaling pathway as ligand. DLK1 was abnormally expressed in a variety of tumors, affecting tumorigenesis and developments. The biological function of DLK1 toward cell proliferation and signaling activation was controversial across different cell types. Two currently known isoforms of DLK1, which are membrane-tethered isoform and soluble isoform, are believed to be the key of DLK1 dual behaviors. While these isoforms are not enough to explain the phenomena, our observations offer the possibility of a third isoform of DLK1. In the present study, we verified the nuclear localization of DLK1 in lung cancer cells. The nuclear localized DLK1 was observed in 107 of 351 non-small cell lung cancer (NSCLC) samples and was associated with tissue differentiation and tumor size. Through co-immunoprecipitation (co-IP) combined mass spectrometry (MS), we identified nuclear receptor corepressor 1 (NCOR1) as DLK1's novel interaction protein and confirmed their interaction in nuclear. We analyzed the expression of NCOR1 in two independent cohorts and demonstrated that NCOR1 is a tumor suppressor and has prognosis potential in lung squamous carcinomas. At last, we analyzed the colocalization of DLK1 and NCOR1 in 147 NSCLC samples by immunohistochemistry (IHC). The result indicated NCOR1 might participate with nuclear localized DLK1 in regulating cell differentiation.

SNP mutation-related genes in breast cancer for monitoring and prognosis of patients: A study based on the TCGA database

Advances in cancer biology have allowed early diagnosis and more comprehensive treatment of breast cancer (BC). However, it remains the most common cause of cancer death in women worldwide because of its strong invasiveness and metastasis. In‐depth study of the molecular pathogenesis of BC and of relevant prognostic markers would improve the quality of life and prognosis of patients. In this study, bioinformatics analysis of SNP‐related data from BC patients provided in the TCGA database revealed that six mutant genes (NCOR1, GATA3, CDH1, ATM, AKT1, and PTEN) were significantly associated with the corresponding expression levels of the proteins. The proteins were involved in multiple pathways related to the development of cancer, including the PI3K‐Akt signaling pathway, pertinent microRNAs, and the MAPK signaling pathway. In addition, overall survival and recurrence‐free survival analysis revealed the close associations of the expression of GATA3, NCOR1, CDH1, and ATM with survival of BC patients. Therefore, detecting these gene mutations and exploring their corresponding expression could be valuable in predicting the prognosis of patients. The results of the high‐throughput data mining provide important fundamental bioinformatics information and a relevant theoretical basis for further exploring the molecular pathogenesis of BC and assessing the prognosis of patients.