Cancer Gene Research Articles

A modified model of PANoptosisto identify prognosis and immunotherapy response in bladder cancer

BackgroundCell death, including apoptosis and necrosis, collectively known as widespread apoptosis. The present study aims to investigate the mechanism of action in widespread apoptosis-related modification patterns in bladder cancer. MethodsUsing a clinical genomics database, we obtained transcriptomic data and related clinical information of bladder cancer patients. By employing the least absolute shrinkage analysis, we were able to construct a risk model and single-cell sequencing analysis of differential genes in bladder cancer. ResultsFive differentially expressed genes (TMPRSS4, TPST1, FOXD1, ELOVL4, EMP1) associated with widespread apoptosis were identified as features for predicting the prognosis of bladder cancer patients. Survival curve analysis revealed significant differences in prognosis (P<0.05). Additionally, multivariate Cox regression analysis determined the independent risk factor for bladder cancer prognosis as the risk score (P<0.001), with high confidence in the scoring model validated internally (P<0.001). Single-cell sequencing reveals high expression of CDKN2A, ERBB2, and TMPRSS4 in B cells, while HRAS is significantly expressed in fibroblasts. ConclusionPANscore, as a potential prognostic and immunotherapeutic biomarker, will provide more precise and rational basis for personalized treatment strategies

Overexpression of NR1D1 portends disease recurrence in thyroid cancer.

Dysregulation of circadian rhythms has been linked to cancer susceptibility. Thyroid cancer cells demonstrate altered circadian oscillations in endogenous clock transcripts. Our previous research identified NR1D1, a component of the circadian clock, as one of the recurrence-associated genes in papillary thyroid cancer. The objective of this study was to investigate the expression pattern of NR1D1 in thyroid cancer and explore its prognostic and translational implications. We assessed NR1D1 expression using immunohistochemical analysis and examined its correlation with clinicopathological parameters. In vitro and in vivo experiments were performed to elucidate the oncogenic roles of NR1D1 and potential mechanisms. Nuclear NR1D1 expression was present in thyroid follicular epithelial-derived cancers, whereas normal thyroid tissue and benign nodular goiter showed no detectable NR1D1 immunoreactivity. Patients with high expression of NR1D1 had more advanced disease stages, extrathyroidal extension, lymphovascular invasion, and shorter recurrence-free survival compared to those with low levels of NR1D1. Through gain- and loss-of-function studies, we demonstrated that NR1D1 modulation affected the growth of organoids, resistance to anoikis, and the invasive and migratory capacity of thyroid cancer cells. The invasion-promoting effect of NR1D1 was regulated by the β-catenin/ZEB1 axis. Moreover, the overexpression of NR1D1 accelerated xenograft growth and lung metastasis in vivo. NR1D1 is overexpressed in malignant thyroid tumors and has prognostic significance. Our findings suggest therapeutic potential in targeting NR1D1 for thyroid cancer.

Utilizing Adenovirus Knob Proteins as Carriers in Cancer Gene Therapy Amidst the Presence of Anti-Knob Antibodies.

Numerous gene therapy drugs for cancer have received global approval, yet their efficacy against solid tumors remains inadequate. Our previous research indicated that the fiber protein, a component of the adenovirus capsid, can propagate from infected cells to neighboring cells that express the adenovirus receptor. We hypothesize that merging this fiber protein with an anti-cancer protein could enable the anti-cancer protein to disseminate around the transfected cells, presenting a novel approach to cancer gene therapy. In our study, we discovered that the knob region of the adenovirus type 5 fiber protein is the smallest unit capable of spreading to adjacent cells in a receptor-specific manner. We also showed that the recombinant knob protein infiltrates cells after dispersing to surrounding cells. To assess the potential of the knob protein to augment gene therapy for solid tumors in mice, we expressed a fusion gene of the A subunit of cytotoxic cholera toxin and the knob region in mouse tumors. We found that this fusion protein only inhibited tumor growth in receptor-expressing mouse melanomas, and this inhibitory effect persisted even in mice with anti-knob antibodies. Our study's findings propose a novel cancer gene therapy strategy that enhances therapeutic effects by specifically delivering therapeutic proteins, expressed from in vivo administered genes, to target molecules. This outcome offers a fresh perspective on gene therapy for solid cancers, and we anticipate that knob proteins will serve as a platform for this method.

Dynamic Mode Decomposition-Based Features for Ovarian Cancer Gene Expression Classification Using Machine Learning

Machine learning (ML) algorithms have been deployed in recent years as models for the analysis of complex data. The ubiquity of ML algorithms stems from their ability to learn the patterns and structures inherent in data. Additionally, they are adaptable to a wide range of data types, irrespective of size, which allows them to learn and predict the future pattern of data. In this work, dynamic mode decomposition (DMD), an ML algorithm, is deployed to analyse the pattern of gene expression data from patients with and without ovarian cancer. Ovarian cancer is one of the deadliest gynaecologic cancers worldwide. The obscure nature of the symptoms makes early detection of ovarian cancer difficult. Early diagnosis increases the chances of survival for patients. Furthermore, the modes computed from DMD are used as features and separately fed into three ML classifiers- support vector machine (SVM), decision tree (DecTr), and K- nearest neighbour (KNN) to classify the gene expression into either cancer or non-cancer categories. Multiple metrics- sensitivity, accuracy, precision, and error rate are used to assess the performance of the models, to have a balanced illustration of a model’s performance. The DecTr outperforms the other two classifiersSVM and KNN, across the metrics used in evaluating the performance of the models.

Identification of SLC22A17 DNA methylation hotspot as a potential biomarker in cutaneous melanoma

BackgroundCancer onset and progression are driven by genetic and epigenetic alterations leading to oncogene activation and the silencing of tumor suppressor genes. Among epigenetic mechanisms, DNA methylation (methDNA) is gaining growing interest in cancer. Promoter hypomethylation is associated with oncogene activation while intragenic methDNA can be involved in transcriptional elongation, alternative spicing, and the activation of cryptic start sites. Several genes involved in the modulation of the tumor microenvironment are regulated by methDNA, including the Solute Carrier Family 22 Member 17 (SLC22A17), which is involved in iron trafficking and extracellular matrix remodeling cooperating with the Gelatinase-Associated Lipocalin (NGAL) ligand. However, the exact role of intragenic methDNA in cancer has not been fully investigated. Therefore, the aim of the present study is to explore the role of methDNA in the regulation of SLC22A17 in cutaneous melanoma (CM), used as a tumor model.MethodsCorrelation and differential analyses between SLC22A17 expression and methDNA were performed using the data contained in The Cancer Genome Atlas and Gene Expression Omnibus databases. Functional studies on melanoma cell lines treated with 5-Azacytidine (5-Aza) were conducted to assess the correlation between methDNA and SLC22A17 expression. A validation study on the diagnostic potential of the in silico-identified SLC22A17 methDNA hotspot was finally performed by analyzing tissue samples obtained from CM patients and healthy controls.ResultsThe computational analyses revealed that SLC22A17 was significantly downregulated in CM, and its expression was related to promoter hypomethylation and intragenic hypermethylation. Moreover, SLC22A17 overexpression and hypermethylation of two intragenic methDNA hotspots were associated with a better clinical outcome in CM patients. The correlation between SLC22A17 methDNA and expression was confirmed in 5-Aza-treated cells. In agreement with in silico analyses, the SLC22A17 promoter methylation hotspot showed higher methDNA levels in CM samples compared to nevi. In addition, the methDNA levels of this hotspot were positively correlated with advanced CM.ConclusionsThe SLC22A17 methDNA hotspot could represent a promising biomarker for CM, highlighting the regulatory role of methDNA on SLC22A17 expression. These results pave the way for the identification of novel epigenetic biomarkers and therapeutic targets for the management of CM patients.

Smart Accumulating Dual-Targeting Lipid Envelopes Equipping Oncolytic Adenovirus for Enhancing Cancer Gene Therapeutic Efficacy.

Systemic delivery of oncolytic adenovirus (oAd) for cancer gene therapy must overcome several limitations such as rapid clearance from the blood, nonspecific accumulation in the liver, and insufficient delivery to the tumor tissues. In the present report, a tumor microenvironment-triggered artificial lipid envelope composed of a pH-responsive sulfamethazine-based polymer (PUSSM)-conjugated phospholipid (DOPE-HZ-PUSSM) and another lipid decorated with epidermal growth factor receptor (EGFR) targeting peptide (GE11) (GE11-DOPE) was utilized to encapsulate replication-incompetent Ad (dAd) or oAd coexpressing short-hairpin RNA (shRNA) against Wnt5 (shWnt5) and decorin (dAd/LP-GE-PS or oAd/LP-GE-PS, respectively). In vitro studies demonstrated that dAd/LP-GE-PS transduced breast cancer cells in a pH-responsive and EGFR-specific manner, showing a higher level of transduction than naked Ad under a mildly acidic pH of 6.0 in EGFR-positive cell lines. In vivo biodistribution analyses revealed that systemic administration of oAd/LP-GE-PS leads to a significantly higher level of intratumoral virion accumulation compared to naked oAd, oAd encapsulated in a liposome without PUSSM or EGFR targeting peptide moiety (oAd/LP), or oAd encapsulated in a liposome with EGFR targeting peptide alone (oAd/LP-GE) in an EGFR overexpressing MDA-MB-468 breast tumor xenograft model, showing that both pH sensitivity and EGFR targeting ability were integral to effective systemic delivery of oAd. Further, systemic administration of all liposomal oAd formulations (oAd/LP, oAd/LP-GE, and oAd/LP-GE-PS) showed significantly attenuated hepatic accumulation of the virus compared to naked oAd. Collectively, our findings demonstrated that pH-sensitive and EGFR-targeted liposomal systemic delivery of oAd can be a promising strategy to address the conventional limitations of oAd to effectively treat EGFR-positive cancer in a safe manner.

Application of integrin subunit genes in pancreatic cancer and the construction of a prognosis model

Application of integrin subunit genes in pancreatic cancer and the construction of a prognosis model

Clinicopathological Study of Prostate Diseases and Its Correlation with PSA Level, Size of Prostate and Gleason’s Scoring System in Case of Prostatic Carcinoma

Background: Prostate gland diseases significantly impact adult males globally, with an increasing prevalence due to aging populations. The primary conditions affecting the prostate are inflammation, benign prostatic hyperplasia (BPH), and tumors, with BPH being the most common. Prostatic carcinoma is also prevalent, with a high lifetime risk. Prostate cancer incidence increases with age, and early detection relies on digital rectal examination, transrectal ultrasonography, and PSA testing. Aim of the study: The study aims to find out correlation between PSA, Gleasons scoring system and HER-2/NEU gene in prostatic cancer. Methods: This study, conducted from July 2017 to June 2019 at BIRDEM General Hospital, enrolled 110 male patients aged 50-100 with clinical signs of prostatic diseases. Patients provided written informed consent and met specific inclusion criteria. Specimens were obtained via TURP, simple or radical prostatectomy, preserved in 10% neutral buffered formalin and examined for pathological lesions. PSA levels were measured using an immunoassay, and Gleason scoring was used for carcinoma categorization. Data were collected via questionnaires and analyzed using SPSS software. Result: The study analyzed 110 prostatic disease cases, with patients averaging 67.7 years. The most common diagnosis was BPH with inflammation (50.9%), followed by BPH without inflammation (35.5%) and adenocarcinoma (13.6%). Urgency (80%), increased micturition frequency (78.2%), poor stream (78.2%), and urinary retention (77.3%) were the most common symptoms. There was a significant correlation between serum PSA levels and prostate size (p &lt; 0.001), with higher PSA levels indicating larger prostates and a higher likelihood of adenocarcinoma. The most frequent Gleason score was 4+4=8 (40%). HER2/neu overexpression showed a marginal correlation with PSA levels (p=0.053). Conclusion: The study found that the most common age group for prostatic diseases was 61-70 years. Benign prostatic hyperplasia (BPH) was the most frequent lesion. Grade II (31-50g) prostate size was common on ultrasound. Most patients had a PSA level of 0-5 ng/ml, aiding early diagnosis and reducing morbidity

Computational Insights into Irinotecan's Interaction with UBE2I in Ovarian and Endometrial Cancers

Endometrial and Ovarian cancers are two highly prevalent and fatal reproductive diseases with poor prognoses among women. Elevated estrogen levels in Ovarian Cancer (OC) stimulate the endometrium, causing Endometrial Cancer (EC). Although numerous studies have reported the crucial genes and pathways in this cancer, the pathogenesis of this disease remains unclear. In this study, used bioinformatics tools to analyse GSE63678, GSE115810, GSE36389, GSE26712, GSE36668, GSE27651, GSE6008, GSE69429, GSE69428, GSE18521, GSE185209, GSE54388 gene expression microarray datasets for both the cancers. We analyzed the differential gene expression, functional association, and structural studies. The analysis identified crucial differentially expressed genes (DEGs) in both cancers associated with DNA damage, DNA integrity, and cell-cycle checkpoint signaling pathways. CLDN7, UBE2I, WT1, JAM2, FOXL2, F11R, JAM3, ZFPM2, MEF2C, and PIAS1 are the top 10 hub genes commonly identified in both cancer types. Only CLDN7 and F11R are upregulated, whereas the remaining hub genes are downregulated in both cancers, suggesting a common framework for contributing to tumorigenesis. Molecular docking and dynamics were performed on the UBE2I protein with Irinotecan Hydrochloride, which could serve as the new approach for treating and managing both cancers. The study reveals the common molecular pathways, pointing out the role of cell cycle and DNA damage and integrity checkpoint signaling in the pathogenesis of both cancer types. This study explored the UBE2I gene as a potential biomarker in OC and EC. Further, this study concludes that the irinotecan hydrochloride drug has higher therapeutic effects on UBE2I protein through docking and dynamics studies.

Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach.

Gastric cancer predominantly adenocarcinoma, accounts for over 85% of gastric cancer diagnoses. Current therapeutic options are limited, necessitating the discovery of novel drug targets and effective treatments. The Affymetrix gene expression microarray dataset (GSE64951) was retrieved from NCBI-GEO data normalization and DEGs identification was done by using R-Bioconductor package. Gene Ontology (GO) analysis of DEGs was performed using DAVID. The protein-protein interaction network was constructed by STRING database plugin in Cytoscape. Subclusters/modules of important interacting genes in main network were extracted by using MCODE. The hub genes from in the network were identified by using Cytohubba. The miRNet tool built a hub gene/mRNA-miRNA network and Kaplan-Meier-Plotter conducted survival analysis. AutoDock Vina and GROMACS MD simulations were used for docking and stability analysis of marine compounds against the 5CNN protein. Total 734 DEGs (507 up-regulated and 228 down-regulated) were identified. Differentially expressed genes (DEGs) were enriched in processes like cell-cell adhesion and ATP binding. Eight hub genes (EGFR, HSPA90AA1, MAPK1, HSPA4, PPP2CA, CDKN2A, CDC20, and ATM) were selected for further analysis. A total of 23 miRNAs associated with hub genes were identified, with 12 of them targeting PPP2CA. EGFR displayed the highest expression and hazard rate in survival analyses. The kinase domain of EGFR (PDBID: 5CNN) was chosen as the drug target. Adociaquinone A from Petrosia alfiani, docked with 5CNN, showed the lowest binding energy with stable interactions across a 50 ns MD simulation, highlighting its potential as a lead molecule against EGFR. This study has identified crucial DEGs and hub genes in gastric cancer, proposing novel therapeutic targets. Specifically, Adociaquinone A demonstrates promising potential as a bioactive drug against EGFR in gastric cancer, warranting further investigation. The predicted miRNA against the hub gene/proteins can also be used as potential therapeutic targets.

ERBB2 is a potential diagnostic and prognostic biomarker in renal clear cell carcinoma

Renal clear cell carcinoma (ccRCC) is a common parenchymal tumor of the kidney, and the discovery of biomarkers for early and effective diagnosis of ccRCC can improve the early diagnosis of patients and thus improve long-term survival. Erb-b2 receptor tyrosine kinase 2 (ERBB2) mediates the processes of cell proliferation, differentiation, and apoptosis inhibition. The purpose of this study was to investigate the diagnostic and prognostic role of ERBB2 in ccRCC. We analyzed the expression levels of ERBB2 in various cancers from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. RNA-seq data were analyzed using R packages to identify differentially expressed genes between the high and low ERBB2 expression groups in the TCGA-KIRC dataset. Spearman correlation analysis was performed to determine the correlation between ERBB2 expression and immune cell infiltration, immune checkpoint expression, and PTEN expression. DNA methylation changes and genetic alterations in ERBB2 were assessed using the MethSurv and cBioPortal databases. Logistic regression analysis was performed to determine the correlation between ERBB2 expression and the clinicopathological characteristics of ccRCC patients. The diagnostic and prognostic value of ERBB2 was assessed using Kaplan‒Meier (K‒M) survival curves, diagnostic ROC curves, time-dependent ROC curves, nomogram models, and Cox regression models. The expression level of ERBB2 is lower in tumor tissues of ccRCC patients than in the corresponding control tissues. Differentially expressed genes associated with ERBB2 were significantly enriched in the pathways “BMP2WNT4FOXO1 pathway in primary endometrial stromal cell differentiation” and “AMAN pathway”. In ccRCC tissues, ERBB2 expression levels were associated with immune cell infiltration, immune checkpoints, and PTEN. The DNA methylation status of 10 CpG islands in the ERBB2 gene was associated with the prognosis of ccRCC. ERBB2 expression levels in ccRCC tissues were associated with race, sex, T stage, M stage, histological grade, and pathological stage. Cox regression analysis showed that ERBB2 was a potential independent predictor of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in ccRCC patients. ROC curve analysis showed that the expression level of ERBB2 could accurately distinguish between ccRCC tissue and adjacent normal renal tissue. Our study showed that ERBB2 expression in ccRCC tissues can be of clinical importance as a potential diagnostic and prognostic biomarker.

Construction and experimental verification of a novel nine-glycosylation-related gene prognostic risk model for clear cell renal carcinoma

ObjectivePatients with clear cell renal carcinoma (ccRCC) typically have poor prognosis. Glycosylation modification plays an important role in ccRCC. This study aimed to develop a novel signature for predicting ccRCC prognosis based on glycosylation-related genes (GRGs). MethodsDifferentially expressed GRGs (DE_GRGs) were identified using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus and used for constructing the risk model. The function of key genes was validated. ResultsTwenty-two DE_GRGs were intersected between GSE53757 and TCGA. Patients with ccRCC were divided into two clusters based on the expression profile of these DE_GRGs. Significant differences in the infiltration of 10 immune cell types were observed between two subclusters. Subsequently, the prognostic signatures of nine DE_GRGs (CHST9, COLGALT1, FUT3, FUT6, HS3ST2, POMGNT2, ST8SIA4, UGT3A1, and UGT8) were established. Patients in the high-risk group showed a poorer prognosis relative to the low-risk group. According to univariate and multivariate Cox regression analyses, the risk score, stage, and grade could be independent prognostic factors. A nomogram incorporating information on gender, age, risk group, TNM stage, and clinical stage showed accurate prediction in the survival probability. Except for CHST9, HS3ST2, and ST8SIA4, expression patterns of the remaining 6 DE_GRGs in Caki-1and 786-O cells were confirmed by quantitative real-time PCR. FUT6 overexpression resulted in the inhibition of proliferation, migration, and invasion of ccRCC cells. ConclusionThis study established a nine-DE_GRG-based prognostic signature, which independently predicted ccRCC prognosis. This finding emphasizes that GRGs are stratification factors for the precise prognosis of ccRCC.

A Risk Model Developed based on Homologous Recombination Deficiency Genes for Evaluating the Drug Sensitivity and Prognostic Prediction of Lung Adenocarcinoma.

This study was designed to construct a risk model based on homologous recombination deficiency (HRD) to evaluate the prognosis and drug sensitivity for patients with lung adenocarcinoma (LUAD). LUAD is a subtype of lung cancer with unfavorable overall survival (OS) and prognosis. HRD has been widely studied in various tumors, but its role in LUAD has not been fully understood. We aimed to construct an HRD-related risk model for predicting the prognosis and drug sensitivity of patients with LUAD. Gene expression data of the LUAD samples were collected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We extracted HRD genes from previous literature and performed univariate COX analysis to select those closely associated with LUAD prognosis. ConsensusClusterPlus was employed to stratify the samples in the TCGA-LUAD cohort into different subtypes. A RiskScore model was established applying random forest method. Furthermore, immunotherapy response and drug sensitivity were predicted using Tumor Immune Dysfunction and Exclusion (TIDE) software and pRRophytic R package, respectively. Finally, the clinical features between High- and Low- RiskScore groups were compared. A total of 16 HRD genes relevant to LUAD prognosis were selected and used to classify 3 LUAD clusters (C1, C2, and C3). Specifically, C1, with a lower TIDE score displayed higher immune infiltration and immunotherapy benefit and the optimal OS, while C2 was closely correlated with tumor-relevant pathways and had the worst OS. Finally, 4 HRD genes (RAD51AP1, BRCA1, H2AFX, and FANCL) were determined to develop a RiskScore signature. It was found that a higher RiskScore was related to more advanced stages, worse OS, and tumor development pathways. Additionally, the High-RiskScore group with a higher TIDE score was sensitive to 44 traditional chemotherapy drugs. A nomogram combined with RiskScore exhibited an accurate survival prediction ability. The HRD-based RiskScore played a crucial role in LUAD development, showing a strong potential to serve as a prognostic indicator for LUAD. Our findings contributed to the diagnosis of LUAD and its treatment.

A dual-signal biosensor based on surface-enhanced Raman spectroscopy for high-sensitivity quantitative detection and imaging of circRNA in living cells

Circular RNAs (circRNAs) are non-coding RNAs that play key roles in the development and progression of cancer through various mechanisms of action, making them promising biomarkers for cancer diagnosis, prognosis, and treatment. In the present study, a biosensor based on surface-enhanced Raman spectroscopy (SERS) was developed for rapid, simple, and sensitive quantitative detection of intracellular circRNAs for the first time. A dual-signal SERS nanoprobe with a 4MBN and ROX signal molecule was fabricated, and the ROX signal intensity was used to determine the concentration of target circSATB2. 4MBN was used as an internal standard to calibrate the ROX signal, thereby achieving highly sensitive and reliable detection of the target circRNA with a limit of detection of 0.043 pM. Furthermore, the relatively high expression of circSATB2 in lung cancer cells compared to that in normal lung epithelial cells was successfully characterized by the proposed SERS imaging method, which is consistent with the results of standard reverse transcription-polymerase chain reaction (RT-PCR). Monitoring of specific circRNAs using this SERS-based biosensor is a promising method for cancer diagnosis and gene therapy.

Methylation, Gene Expression, and Risk Genotypes at the TERT-CLPTM1L Locus in Cervical Cancer.

The reverse transcriptase subunit of telomerase, TERT, is frequently activated in high-grade dysplasia and invasive cancers of the uterine cervix. Telomerase activation through hypomethylation of the TERT promoter holds promise as a biomarker for cervical cancer progression, however, specific CpG sites involved in cervical cancer risk remain to be fully defined. A recent genome-wide association study on cervical cancer identified genetic polymorphisms at 5p13.33 (close to TERT-CLPTM1L) but the underlying mechanisms are undetermined. We investigated 529 CpG sites within the TERT promoter region and 3 CpG islands nearby, and 21 CpG sites within CLPTM1L in 190 bisulfite-converted cervical tumor DNA samples from BioRAIDs (NCT02428842). We identified eight CpG sites within TERT intron 2 where methylation was significantly associated with the genotypes of cervical cancer risk variants rs27070 and rs459961 in cervical tumors after multiple testing correction (p < 9.4 × 10E-5). Hypermethylation at chr5:1289663 correlated with decreased TERT mRNA levels. In an independent series of 188 normal or dysplastic cervical tissues, rare alleles of rs27070 and rs459961 were associated with low basal CLPTM1L levels and with the absence of TERT mRNA in HPV-negative samples, consistent with their proposed role as protective variants for cervical cancer. HPV infection was associated with increased CLPTM1L and TERT levels. Collectively, our results provide a link between cervical cancer risk variants, methylation, and gene expression and implicate both TERT and CLPTM1L as genes modulated by genomic background and HPV infection during cervical cancer development.

Long-read sequencing of an advanced cancer cohort resolves rearrangements, unravels haplotypes, and reveals methylation landscapes.

The Long-Read Personalized OncoGenomics (POG) dataset comprises a cohort of 189 patient tumors and 41 matched normal samples sequenced using the Oxford Nanopore Technologies PromethION platform. This dataset from the POG program and the Marathon of Hope Cancer Centres Network includes DNA and RNA short-read sequence data, analytics, and clinical information. We show the potential of long-read sequencing for resolving complex cancer-related structural variants, viral integrations, and extrachromosomal circular DNA. Long-range phasing facilitates the discovery of allelically differentially methylated regions (aDMRs) and allele-specific expression, including recurrent aDMRs in the cancer genes RET and CDKN2A. Germline promoter methylation in MLH1 can be directly observed in Lynch syndrome. Promoter methylation in BRCA1 and RAD51C is a likely driver behind homologous recombination deficiency where no coding driver mutation was found. This dataset demonstrates applications for long-read sequencing in precision medicine and is available as a resource for developing analytical approaches using this technology.

In silico screening and identifying phytoconstituents of Withania somnifera as potent inhibitors of BRCA1 mutants: A therapeutic against breast cancer

Breast CAncer gene 1 (BRCA1) is an anti-oncogene that helps the cell repair damaged DNA and preserve genetic material. BRCA1 also acts as a cell growth suppressor and produces tumor suppressor gene (TSG) proteins, i.e., BRCA1 protein. Remarkably, BRCA1 mutations account for 90 % of hereditary breast cancer and a majority of hereditary ovarian cancer. Hence, we have considered three mutants of BRCA1 (R1699W, R1699Q, T1700A) in this study and adopted an in-silico approach to find the best possible phytochemical to inhibit these mutated proteins, enabling early breast cancer diagnosis. Perceiving the importance, many natural molecules from ancient medicinal plants are considered for molecular docking. Our findings suggest that though many molecules bind actively with the receptor's active site, the top three phytoconstituents (27-Deoxy-14-hydroxywithaferin A, Withacoagulin, Somniferanolide) of Withania somnifera, commonly known as Ashwagandha, have high binding affinities and suitable pharmacokinetic properties, making these natural compounds potential drug candidates. Further, molecular dynamics (MD) simulation and the binding free energy calculation show stability and thermodynamically favourable. We can, therefore, draw the conclusion that these lead compounds act as potential inhibitors against BRCA1. However, wet lab experiments and clinical trials are recommended to ascertain its efficacy, hence the development of novel BRCA1 inhibitors.

CDX2-Suppressed Colorectal Cancers Possess Potentially Targetable Alterations in Receptor Tyrosine Kinases and Other Colorectal-Cancer-Associated Pathways.

Colorectal cancer, a prevalent gastrointestinal carcinoma, has a high risk for recurrence when locally advanced and remains lethal when in an advanced stage. Prognostic biomarkers may help in better delineating the aggressiveness of this disease in individual patients and help to tailor appropriate therapies. CDX2, a transcription factor of gastrointestinal differentiation, has been proposed as a biomarker for good outcomes and could also be a marker of specific sub-types amenable to targeted therapies. Colorectal cancers from The Cancer Genome Atlas (TCGA) colorectal cohort and colon cancers from the Sidra-LUMC AC-ICAM cohort were categorized according to their expressions of CDX2 mRNA. Groups with CDX2 suppression were compared with cancers showing no suppression regarding their clinical and genomic characteristics. CDX2-suppressed colorectal cancers showed a high prevalence of Microsatellite Instability (MSI) and a lower prevalence of chromosomal Instability (CIN) compared to non-CDX2-suppressed cancers. In addition, CDX2-suppressed cancers had a higher prevalence of mutations in several receptor tyrosine kinase genes, including EGFR, ERBB3, ERBB4, RET, and ROS1. In contrast, CDX2-suppressed cancers displayed lower mutation frequencies than non-CDX2-suppressed cancers in the genes encoding for the two most frequently mutated tumor suppressors, APC and TP53, and the most frequently mutated colorectal cancer oncogene, KRAS. However, CDX2-suppressed colorectal cancers had a higher prevalence of mutations in alternative genes of the WNT/APC/β-catenin and KRAS/BRAF/MEK pathways. In addition, they showed frequent mutations in DNA damage response (DDR) genes, such as BRCA2 and ATM. CDX2-suppressed colorectal cancers constitute a genomically distinct subset of colon and rectal cancers that have a lower prevalence of KRAS, APC, and TP53 mutations, but a high prevalence of mutations in less commonly mutated colorectal cancer genes. These alterations could serve as targets for personalized therapeutics in this subset.

Multi-omics analysis reveals BZW1's regulation of EMT via the Wnt pathway in lung adenocarcinoma.

Exploring the role of novel cancer gene BZW1 in lung adenocarcinoma (LUAD) and unveiling associated signalling pathways. Firstly, we conducted a pan-cancer analysis of BZW1 using multiple databases. Subsequently, leveraging single-cell data from LUAD, we successfully uncovered potential oncological processes associated with BZW1 and further validated them through experimentation. Simultaneously, we continued to investigate the potential molecular mechanisms underlying the oncological processes mediated by BZW1. Additionally, we employed various machine learning algorithms to construct prognostic models concerning BZW1 and the epithelial-mesenchymal transition (EMT) process. Our research firstly demonstrated the elevated expression of BZW1 in various cancer cells. Leveraging single-cell data from LUAD, we identified that BZW1 regulates the occurrence of EMT in LUAD, a phenomenon validated across multiple LUAD cell lines. Moreover, we further discovered that BZW1 regulates LUAD's EMT process through the Wnt/β-catenin signalling pathway. Lastly, we successfully constructed prognostic models using BZW1-related genes and EMT genes.

Delivery of doxorubicin by Fe3O4 nanoparticles, reduces multidrug resistance gene expression in ovarian cancer cells

BackgroundOvarian cancer is one of the most common malignancy in women with significant mortality rate due to the resistance to chemotherapy drugs. Doxorubicin (DOX) is a chemotropic agent in ovarian cancer treatment. Overexpression of multidrug resistance (MDR) genes, such as ABCB1, in cancer cells after chemotherapy is one of main problems in clinical applications. Here we have compared the efficiency of doxorubicin-loaded (NIPAAM-DMAEMA) Fe3O4 nanocomposite (DOX-NANO) against DOX on ABCB1(MDR1) gene expression in the ovarian cancer cell line. Materials and MethodsThe cell viability of SKOV-3 cells were evaluated by MTT assay. Real Time PCR was used to measure the expression level of MDR1. MTT data were normalized in 10 different attribute weighting models, also to reveal the interaction between DOX, ABCB1, and ovarian cancer genes, Pathway Studio Database (Elsevier) was used. ResultsCell viability of SKOV-3cells was significantly decreased after 24, 48 and 72hours (P < 0.0001) of either DOX with IC50 22.38, 0.61 and 0.072µg/ml or DOX-NANO treatment with IC50 11.54, 1.01, 0.0126µg/ ml respectively. treatment. Notable decrease in the expression of MDR gene, ABCB1, was observed 48hours after treatment with DOX-NANO (P < 0.0001) with 26% in the assessed with control group. Meta-analysis showed the concentration of 10μg/ml variables was the second most significant feature, whereas the concentration of 0.01μg/ml recognized the lowest weights. Also, LGALS3 is an extra cellular receptor with upregulation in ovarian cancer that interacts with ABCB1. ConclusionOur findings highlight the beneficial effects of DOX delivery in ovarian cancer cells by nanocomposite as efficient drug delivery method. DOX-NANO is a promising therapeutic reagent to overcome chemotherapy resistance in ovarian cancer.