Gene expression-based biomarkers designating glioblastomas resistant to multiple treatment strategies

Abstract Despite advances in molecular characterization of glioblastoma multiforme (GBM), only a handful of predictive biomarkers exist with limited clinical relevance. We aimed to identify differentially expressed genes in tumor samples collected at surgery associated with response to subsequent treatment, including temozolomide (TMZ) and nitrosoureas. Gene expression was collected from multiple independent datasets. Patients were categorized as responders/nonresponders based on their survival status at 16 months post-surgery. For each gene, the expression was compared between responders and nonresponders with a Mann-Whitney U test and receiver operating characteristic. The package "roc" was used to calculate the area under the curve (AUC). The integrated database comprises 454 GBM patients from three independent datasets and 10,103 genes. The highest proportion of responders (68%) were among patients treated with TMZ combined with nitrosoureas, where FCGR2B upregulation provided the strongest predictive value (AUC=0.72, p < 0.001). Elevated expression of CSTA and MRPS17 was associated with a lack of response to multiple treatment strategies. DLL3 upregulation was present in subsequent responders to any treatment combination containing TMZ. Three genes (PLSCR1, MX1, and MDM2) upregulated both in the younger cohort and in patients expressing low MGMT delineate a subset of patients with worse prognosis within a population generally associated with a favorable outcome. The identified transcriptomic changes provide biomarkers of responsiveness, offer avenues for preclinical studies, and may enhance future GBM patient stratifications. The described methodology provides a reliable pipeline for the initial testing of potential biomarker candidates for future validation studies.

Download Full-text

761 Potential predictive biomarkers of rapid progression and response to anti-PD1 treatment by gene profiling analysis in metastatic melanoma patients

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0761 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A809-A809

Author(s):

Maria Grazia Vitale ◽

Domenico Mallardo ◽

Antonio Grimaldi ◽

Ncholas Bayless ◽

Mariaelena Capone ◽

...

Keyword(s):

Gene Expression ◽

Metastatic Melanoma ◽

Predictive Biomarkers ◽

Gene Profiling ◽

P Value ◽

Specific Gene ◽

Rapid Progression ◽

Potential Biomarker ◽

Melanoma Patients ◽

Profiling Analysis

BackgroundImmunotherapy dramatically changed the landscape of melanoma treatment. Even if nearly 40% of patients has a long-term benefit from anti-PD-1 agents, nearly 30% relapse in the first year of treatment, showing in some cases very rapid disease progression. Actually, there are no effective biomarkers that could predict patient‘s clinical benefit. Aim of this study is to identify gene profiling biomarkers that could help to select melanoma patients who most likely respond to anti-PD-1 therapy.MethodsWe defined as fast responder (FR) or fast progressor (FP) patients who got clinical response or clinical progression within eight weeks from first cycle of therapy. We retrospectively collected data from 51 metastatic melanoma patients (25 FR and 26 FP) treated from October 2016 to June 2020 in first-line with anti-PD1 monotherapy (nivolumab or pembrolizumab) at National Cancer Institute of Naples, Italy. Gene expression profiling analysis was performed using NanoString® IO 360 panels on PBMCs collected at baseline from 18 patients (10 FR and 8 FP). Patients with ECOG≥2 were excluded. They were all IV stage (5 M1a, 1 M1b, 12 M1c) of which 15 were B-RAF wild-type (83%) and 3 were B-RAF mutated (17%). Statistical associations between treatment response and gene score variables were estimated through Bonferroni correction for multiple comparisons and Benjamini-Hochberg.ResultsPatterns of gene expression were assessed for correlation to response. We compared PBMCs Nanostring analysis between FR and FP patients. We found a higher expression of KRas, CD39, IFI16, IL18, FCGR2A, IL1RN, MAP3K8, TLR5, TLR8, MyD88 and NF-kB in FP patients (all with p-value ≤0.005), most of them related to cell proliferation and immunosuppressive mechanism. Instead we found a higher expression of PRF1, PIK3R1, HLA-DPA1, HLA-DRB1, HLA-DOA, CD45RA, LDHB, KIR3DL2, CD2, CD28, CD7, CD27 in FR patients (all with p-value ≤0.01), most of them related to priming and cytolysis.ConclusionsOur study suggests that a specific gene signature may discriminate FR or FP patients. These preliminary data provide a rationale for further investigating gene profiling signature as a potential biomarker of response to immunotherapy.AcknowledgementsThe study was supported by the Institutional Project ‘Ricerca Corrente’ of Istituto Nazionale Tumori IRCCS Fondazione ‘G. Pascale’ of Napoli, Italy.Ethics ApprovalThe study was approved by the internal ethics board of the Istituto Nazionale Tumori IRCCS Fondazione ‘G. Pascale’ of Napoli Italy, approval number of registry 17/17 OSS.

Download Full-text

Towards Understanding Therapeutic Failures in Masquelet Surgery: First Evidence that Defective Induced Membrane Properties are Associated with Clinical Failures

Journal of Clinical Medicine ◽

10.3390/jcm9020450 ◽

2020 ◽

Vol 9 (2) ◽

pp. 450 ◽

Cited By ~ 5

Author(s):

Marjorie Durand ◽

Laure Barbier ◽

Laurent Mathieu ◽

Thomas Poyot ◽

Thomas Demoures ◽

...

Keyword(s):

Gene Expression ◽

Predictive Biomarkers ◽

Membrane Properties ◽

Cement Spacer ◽

Expression Ratio ◽

Ecm Remodeling ◽

Induced Membrane ◽

Post Surgery ◽

Masquelet Technique ◽

Membrane Technique

The two-stage Masquelet induced-membrane technique (IMT) consists of cement spacer-driven membrane induction followed by an autologous cancellous bone implantation in this membrane to promote large bone defect repairs. For the first time, this study aims at correlating IMT failures with physiological alterations of the induced membrane (IM) in patients. For this purpose, we compared various histological, immunohistochemical and gene expression parameters obtained from IM collected in patients categorized lately as successfully (Responders; n = 8) or unsuccessfully (Non-responders; n = 3) treated with the Masquelet technique (6 month clinical and radiologic post-surgery follow-up). While angiogenesis or macrophage distribution pattern remained unmodified in non-responder IM as compared to responder IM, we evidenced an absence of mesenchymal stem cells and reduced density of fibroblast-like cells in non-responder IM. Furthermore, non-responder IM exhibited altered extracellular matrix (ECM) remodeling parameters such as a lower expression ratio of metalloproteinase-9 (MMP-9)/tissue inhibitor of metalloproteinases (TIMP-1) mRNA as well as an important collagen overexpression as shown by picrosirius red staining. In summary, this study is the first to report evidence that IMT failure can be related to defective IM properties while underlining the importance of ECM remodeling parameters, particularly the MMP-9/TIMP-1 gene expression ratio, as early predictive biomarkers of the IMT outcome regardless of the type of bone, fracture or patient characteristics.

Download Full-text

Cell-centred meta-analysis reveals baseline predictors of anti-TNFα non-response in biopsy and blood of patients with IBD

Gut ◽

10.1136/gutjnl-2017-315494 ◽

2018 ◽

Vol 68 (4) ◽

pp. 604-614 ◽

Cited By ~ 55

Author(s):

Renaud Gaujoux ◽

Elina Starosvetsky ◽

Naama Maimon ◽

Francesco Vallania ◽

Haggai Bar-Yoseph ◽

...

Keyword(s):

Gene Expression ◽

Plasma Cells ◽

Immune Cell ◽

Expression Profiles ◽

Meta Analysis ◽

Area Under The Curve ◽

Predictive Biomarkers ◽

Cost Benefit ◽

Response To Therapy ◽

Necrosis Factor Alpha

ObjectiveAlthough anti-tumour necrosis factor alpha (anti-TNFα) therapies represent a major breakthrough in IBD therapy, their cost–benefit ratio is hampered by an overall 30% non-response rate, adverse side effects and high costs. Thus, finding predictive biomarkers of non-response prior to commencing anti-TNFα therapy is of high value.DesignWe analysed publicly available whole-genome expression profiles of colon biopsies obtained from multiple cohorts of patients with IBD using a combined computational deconvolution—meta-analysis paradigm which allows to estimate immune cell contribution to the measured expression and capture differential regulatory programmes otherwise masked due to variation in cellular composition. Insights from this in silico approach were experimentally validated in biopsies and blood samples of three independent test cohorts.ResultsWe found the proportion of plasma cells as a robust pretreatment biomarker of non-response to therapy, which we validated in two independent cohorts of immune-stained colon biopsies, where a plasma cellular score from inflamed biopsies was predictive of non-response with an area under the curve (AUC) of 82%. Meta-analysis of the cell proportion-adjusted gene expression data suggested that an increase in inflammatory macrophages in anti-TNFα non-responding individuals is associated with the upregulation of the triggering receptor expressed on myeloid cells 1 (TREM-1) and chemokine receptor type 2 (CCR2)-chemokine ligand 7 (CCL7) –axes. Blood gene expression analysis of an independent cohort, identified TREM-1 downregulation in non-responders at baseline, which was predictive of response with an AUC of 94%.ConclusionsOur study proposes two clinically feasible assays, one in biopsy and one in blood, for predicting non-response to anti-TNFα therapy prior to initiation of treatment. Moreover, it suggests that mechanism-driven novel drugs for non-responders should be developed.

Download Full-text

217 Evaluating biomarkers of JTX-8064 (anti-LILRB2/ILT4 monoclonal antibody) in an ex vivo human tumor histoculture system to inform clinical development

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0217 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A236-A236

Author(s):

Yasmin Hashambhoy-Ramsay ◽

Vikki Spaulding ◽

Michelle Priess ◽

Kristin O’Malley ◽

Monica Gostissa ◽

...

Keyword(s):

Gene Expression ◽

Monoclonal Antibody ◽

Head And Neck ◽

Expression Analysis ◽

Gene Expression Analysis ◽

Ex Vivo ◽

Human Tumor ◽

Predictive Biomarkers ◽

Isotype Control ◽

Post Surgery

BackgroundLeukocyte immunoglobulin-like receptor B2 (LILRB2; ILT4) is an immunoinhibitory protein expressed on the surface of myeloid cells that has been increasingly recognized as a therapeutic target of interest in immuno-oncology (IO). Upon binding its ligands, MHC I molecules (e.g. HLA-G/HLA-A), LILRB2 inhibits myeloid cell activation and promotes an M2-like (anti-inflammatory) state. LILRB2 was the first target prioritized from a macrophage discovery effort leading to the development of JTX-8064, a humanized monoclonal antibody that specifically binds to and antagonizes LILRB2. JTX-8064 has been shown to induce an M1-like (pro-inflammatory; anti-tumor) functional state in macrophages. Rodents do not express LILRB proteins limiting their usefulness as a model for preclinical study of JTX-8064. To overcome this limitation, we conducted an ex vivo human tumor histoculture study to assess the pharmacodynamic effects of LILRB2 antagonism. Protein and/or gene expression analysis of matched tumor samples enabled the discovery of predictive biomarkers associated with the induction of specific pharmacodynamic signatures in ex vivo-cultured human tumors in response to JTX-8064. Finally, tumor types were identified that had a high prevalence of these predictive biomarkers suggesting they may be priority indications for JTX-8064 therapy.MethodsMore than 100 fresh treatment-naïve human tumor samples obtained post-surgery from kidney, lung, and head and neck cancer were treated with JTX-8064 or isotype control antibody for 24 hrs in the histoculture system. RNA was isolated from tumors prior to any treatment as well as from JTX-8064 and isotype control treated samples. Gene expression was analyzed using the NanoString nCounter® and qPCR assays. Additional IHC analyses were performed on baseline untreated tumor samples.ResultsJTX-8064 was shown to induce pharmacodynamic responses to treatment significantly above isotype control indicative of macrophage polarization, IFNg-signaling, and T cell inflammation. To identify predictive biomarkers of pharmacodynamic response to JTX-8064, matched untreated samples were characterized by gene expression analysis and by IHC (CD8, CD163, and HLA-G proteins). Numerous LILRB2 pathway-related molecules (e.g. HLA-A, HLA-B, CD163, LILRB2) and gene signatures were found to be statistically significantly higher in the untreated kidney, head and neck, and lung cancer samples of matched pharmacodynamic responders compared to non-responders. Further bioinformatics analysis revealed additional cancer subtypes where these biomarkers are enriched.ConclusionsThese data will inform indication selection and combination strategies for JTX-8064 to maximize potential therapeutic benefit for patients with solid tumor malignancies.

Download Full-text

An Unbiased Predictive Model to Detect DNA Methylation Propensity of CpG Islands in the Human Genome

Current Bioinformatics ◽

10.2174/1574893615999200724145835 ◽

2020 ◽

Vol 15 ◽

Author(s):

Dicle Yalcin ◽

Hasan H. Otu

Keyword(s):

Model Building ◽

De Novo ◽

Cpg Islands ◽

Treatment Strategies ◽

Area Under The Curve ◽

Global Methylation ◽

Sequence Features ◽

A Genome ◽

Combined Features ◽

Epigenetic Repression

Background: Epigenetic repression mechanisms play an important role in gene regulation, specifically in cancer development. In many cases, a CpG island’s (CGI) susceptibility or resistance to methylation are shown to be contributed by local DNA sequence features. Objective: To develop unbiased machine learning models–individually and combined for different biological features–that predict the methylation propensity of a CGI. Methods: We developed our model consisting of CGI sequence features on a dataset of 75 sequences (28 prone, 47 resistant) representing a genome-wide methylation structure. We tested our model on two independent datasets that are chromosome (132 sequences) and disease (70 sequences) specific. Results: We provided improvements in prediction accuracy over previous models. Our results indicate that combined features better predict the methylation propensity of a CGI (area under the curve (AUC) ~0.81). Our global methylation classifier performs well on independent datasets reaching an AUC of ~0.82 for the complete model and an AUC of ~0.88 for the model using select sequences that better represent their classes in the training set. We report certain de novo motifs and transcription factor binding site (TFBS) motifs that are consistently better in separating prone and resistant CGIs. Conclusion: Predictive models for the methylation propensity of CGIs lead to a better understanding of disease mechanisms and can be used to classify genes based on their tendency to contain methylation prone CGIs, which may lead to preventative treatment strategies. MATLAB and Python™ scripts used for model building, prediction, and downstream analyses are available at https://github.com/dicleyalcin/methylProp_predictor.

Download Full-text

Sphingolipid Analysis Indicate Lactosylceramide as a Potential Biomarker of Inflammatory Bowel Disease in Children

Biomolecules ◽

10.3390/biom10071083 ◽

2020 ◽

Vol 10 (7) ◽

pp. 1083

Author(s):

Aleksandra Filimoniuk ◽

Agnieszka Blachnio-Zabielska ◽

Monika Imierska ◽

Dariusz Marek Lebensztejn ◽

Urszula Daniluk

Keyword(s):

Inflammatory Bowel Disease ◽

Bowel Disease ◽

High Performance ◽

Area Under The Curve ◽

Study Groups ◽

Diagnostic Value ◽

Serum Samples ◽

Specificity And Sensitivity ◽

Potential Biomarker ◽

Inflammatory Bowel

An altered ceramide composition in patients with inflammatory bowel disease (IBD) has been reported recently. The aim of this study was to evaluate the concentrations of sphingolipids in the serum of treatment-naive children with newly diagnosed IBD and to determine the diagnostic value of the tested lipids in pediatric IBD. The concentrations of sphingolipids in serum samples were evaluated using a quantitative method, an ultra-high-performance liquid chromatography-tandem mass spectrometry in children with Crohn’s disease (CD) (n=34), ulcerative colitis (UC) (n = 39), and controls (Ctr) (n = 24). Among the study groups, the most significant differences in concentrations were noted for C16:0-LacCer, especially in children with CD compared to Ctr or even to UC. Additionally, the relevant increase in C20:0-Cer and C18:1-Cer concentrations were detected in both IBD groups compared to Ctr. The enhanced C24:0-Cer level was observed only in UC, while C18:0-Cer only in the CD group. The highest area under the curve (AUC), specificity, and sensitivity were determined for C16:0-LacCer in CD diagnosis. Our results suggest that the serum LacC16-Cer may be a potential biomarker that distinguishes children with IBD from healthy controls and differentiates IBD subtypes. In addition, C20:0-Cer and C18:0-Cer levels also seem to be closely connected with IBD.

Download Full-text

Dysregulations of MicroRNA and Gene Expression in Chronic Venous Disease

Journal of Clinical Medicine ◽

10.3390/jcm9051251 ◽

2020 ◽

Vol 9 (5) ◽

pp. 1251 ◽

Cited By ~ 2

Author(s):

Daniel P. Zalewski ◽

Karol P. Ruszel ◽

Andrzej Stępniewski ◽

Dariusz Gałkowski ◽

Jacek Bogucki ◽

...

Keyword(s):

Gene Expression ◽

Mononuclear Cells ◽

Varicose Veins ◽

Expression Profiles ◽

Lower Limbs ◽

Chronic Venous Disease ◽

Venous Disease ◽

Operating Characteristics ◽

Potential Biomarker ◽

Pathologic Features

Chronic venous disease (CVD) is a vascular disease of lower limbs with high prevalence worldwide. Pathologic features include varicose veins, venous valves dysfunction and skin ulceration resulting from dysfunction of cell proliferation, apoptosis and angiogenesis. These processes are partly regulated by microRNA (miRNA)-dependent modulation of gene expression, pointing to miRNA as a potentially important target in diagnosis and therapy of CVD progression. The aim of the study was to analyze alterations of miRNA and gene expression in CVD, as well as to identify miRNA-mediated changes in gene expression and their potential link to CVD development. Using next generation sequencing, miRNA and gene expression profiles in peripheral blood mononuclear cells of subjects with CVD in relation to healthy controls were studied. Thirty-one miRNAs and 62 genes were recognized as potential biomarkers of CVD using DESeq2, Uninformative Variable Elimination by Partial Least Squares (UVE-PLS) and ROC (Receiver Operating Characteristics) methods. Regulatory interactions between potential biomarker miRNAs and genes were projected. Functional analysis of microRNA-regulated genes revealed terms closely related to cardiovascular diseases and risk factors. The study shed new light on miRNA-dependent regulatory mechanisms involved in the pathology of CVD. MicroRNAs and genes proposed as CVD biomarkers may be used to develop new diagnostic and therapeutic methods.

Download Full-text

DNA methylation and gene expression integration in cardiovascular disease

Clinical Epigenetics ◽

10.1186/s13148-021-01064-y ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Guillermo Palou-Márquez ◽

Isaac Subirana ◽

Lara Nonell ◽

Alba Fernández-Sanlés ◽

Roberto Elosua

Keyword(s):

Gene Expression ◽

Cardiovascular Disease ◽

Dna Methylation ◽

Cardiovascular Diseases ◽

Disease Risk ◽

Cardiovascular Disease Risk ◽

Risk Function ◽

Predictive Biomarkers ◽

Independent Study ◽

Cell Type

Abstract Background The integration of different layers of omics information is an opportunity to tackle the complexity of cardiovascular diseases (CVD) and to identify new predictive biomarkers and potential therapeutic targets. Our aim was to integrate DNA methylation and gene expression data in an effort to identify biomarkers related to cardiovascular disease risk in a community-based population. We accessed data from the Framingham Offspring Study, a cohort study with data on DNA methylation (Infinium HumanMethylation450 BeadChip; Illumina) and gene expression (Human Exon 1.0 ST Array; Affymetrix). Using the MOFA2 R package, we integrated these data to identify biomarkers related to the risk of presenting a cardiovascular event. Results Four independent latent factors (9, 19, 21—only in women—and 27), driven by DNA methylation, were associated with cardiovascular disease independently of classical risk factors and cell-type counts. In a sensitivity analysis, we also identified factor 21 as associated with CVD in women. Factors 9, 21 and 27 were also associated with coronary heart disease risk. Moreover, in a replication effort in an independent study three of the genes included in factor 27 were also present in a factor identified to be associated with myocardial infarction (CDC42BPB, MAN2A2 and RPTOR). Factor 9 was related to age and cell-type proportions; factor 19 was related to age and B cells count; factor 21 pointed to human immunodeficiency virus infection-related pathways and inflammation; and factor 27 was related to lifestyle factors such as alcohol consumption, smoking and body mass index. Inclusion of factor 21 (only in women) improved the discriminative and reclassification capacity of the Framingham classical risk function and factor 27 improved its discrimination. Conclusions Unsupervised multi-omics data integration methods have the potential to provide insights into the pathogenesis of cardiovascular diseases. We identified four independent factors (one only in women) pointing to inflammation, endothelium homeostasis, visceral fat, cardiac remodeling and lifestyles as key players in the determination of cardiovascular risk. Moreover, two of these factors improved the predictive capacity of a classical risk function.

Download Full-text

Optimal Utility of H-Reflex RDD as a Biomarker of Spinal Disinhibition in Painful and Painless Diabetic Neuropathy

Diagnostics ◽

10.3390/diagnostics11071247 ◽

2021 ◽

Vol 11 (7) ◽

pp. 1247

Author(s):

Anne Worthington ◽

Alise Kalteniece ◽

Maryam Ferdousi ◽

Luca Donofrio ◽

Shaishav Dhage ◽

...

Keyword(s):

Diabetic Neuropathy ◽

Characteristic Curve ◽

Area Under The Curve ◽

Initial Response ◽

Healthy Controls ◽

Painful Diabetic Neuropathy ◽

Stimulus Response ◽

Rate Dependent ◽

Potential Biomarker ◽

Spinal Inhibition

Impaired rate-dependent depression of the Hoffman reflex (HRDD) is a potential biomarker of impaired spinal inhibition in patients with painful diabetic neuropathy. However, the optimum stimulus-response parameters that identify patients with spinal disinhibition are currently unknown. We systematically compared HRDD, performed using trains of 10 stimuli at five stimulation frequencies (0.3, 0.5, 1, 2 and 3 Hz), in 42 subjects with painful and 62 subjects with painless diabetic neuropathy with comparable neuropathy severity, and 34 healthy controls. HRDD was calculated using individual and mean responses compared to the initial response. At stimulation frequencies of 1, 2 and 3 Hz, HRDD was significantly impaired in patients with painful diabetic neuropathy compared to patients with painless diabetic neuropathy for all parameters and for most parameters when compared to healthy controls. HRDD was significantly enhanced in patients with painless diabetic neuropathy compared to controls for responses towards the end of the 1 Hz stimulation train. Receiver operating characteristic curve analysis in patients with and without pain showed that the area under the curve was greatest for response averages of stimuli 2–4 and 2–5 at 1 Hz, AUC = 0.84 (95%CI 0.76–0.92). Trains of 5 stimuli delivered at 1 Hz can segregate patients with painful diabetic neuropathy and spinal disinhibition, whereas longer stimulus trains are required to segregate patients with painless diabetic neuropathy and enhanced spinal inhibition.

Download Full-text

The combined detection of Amphiregulin, Cyclin A1 and DDX20/Gemin3 expression predicts aggressive forms of oral squamous cell carcinoma

British Journal of Cancer ◽

10.1038/s41416-021-01491-x ◽

2021 ◽

Author(s):

Ekaterina Bourova-Flin ◽

Samira Derakhshan ◽

Afsaneh Goudarzi ◽

Tao Wang ◽

Anne-Laure Vitte ◽

...

Keyword(s):

Gene Expression ◽

Squamous Cell ◽

Large Scale ◽

Biomarker Discovery ◽

Gene Expression Signature ◽

Predictive Biomarkers ◽

Specific Gene ◽

Specific Expression ◽

Intrinsic Nature ◽

Independent Cohort

Abstract Background Large-scale genetic and epigenetic deregulations enable cancer cells to ectopically activate tissue-specific expression programmes. A specifically designed strategy was applied to oral squamous cell carcinomas (OSCC) in order to detect ectopic gene activations and develop a prognostic stratification test. Methods A dedicated original prognosis biomarker discovery approach was implemented using genome-wide transcriptomic data of OSCC, including training and validation cohorts. Abnormal expressions of silent genes were systematically detected, correlated with survival probabilities and evaluated as predictive biomarkers. The resulting stratification test was confirmed in an independent cohort using immunohistochemistry. Results A specific gene expression signature, including a combination of three genes, AREG, CCNA1 and DDX20, was found associated with high-risk OSCC in univariate and multivariate analyses. It was translated into an immunohistochemistry-based test, which successfully stratified patients of our own independent cohort. Discussion The exploration of the whole gene expression profile characterising aggressive OSCC tumours highlights their enhanced proliferative and poorly differentiated intrinsic nature. Experimental targeting of CCNA1 in OSCC cells is associated with a shift of transcriptomic signature towards the less aggressive form of OSCC, suggesting that CCNA1 could be a good target for therapeutic approaches.

Download Full-text