Onco最新文献

{"title":"Onco: A Promising Player Amidst Oncology Journals","authors":"C. Baxevanis","doi":"10.3390/onco3020009","DOIUrl":"https://doi.org/10.3390/onco3020009","url":null,"abstract":"As the new Editor-in-Chief of the journal, I believe that I must continue the efforts of my predecessor even more actively and with greater enthusiasm and dedication so that the journal becomes a pole of attraction for the publication of excellent studies of basic, translational and clinical research for the treatment of cancer [...]","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47571990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transcriptome Analysis Identifies Tumor Immune Microenvironment Signaling Networks Supporting Metastatic Castration-Resistant Prostate Cancer.","authors":"Lawrence P McKinney, Rajesh Singh, I King Jordan, Sooryanarayana Varambally, Eric B Dammer, James W Lillard","doi":"10.3390/onco3020007","DOIUrl":"10.3390/onco3020007","url":null,"abstract":"<p><p>Prostate cancer (PCa) is the second most common cause of cancer death in American men. Metastatic castration-resistant prostate cancer (mCRPC) is the most lethal form of PCa and preferentially metastasizes to the bones through incompletely understood molecular mechanisms. Herein, we processed RNA sequencing data from patients with mCRPC (<i>n</i> = 60) and identified 14 gene clusters (modules) highly correlated with mCRPC bone metastasis. We used a novel combination of weighted gene co-expression network analysis (WGCNA) and upstream regulator and gene ontology analyses of clinically annotated transcriptomes to identify the genes. The cyan module (M14) had the strongest positive correlation (0.81, <i>p</i> = 4 × 10^-15) with mCRPC bone metastasis. It was associated with two significant biological pathways through KEGG enrichment analysis (parathyroid hormone synthesis, secretion, and action and protein digestion and absorption). In particular, we identified 10 hub genes (<i>ALPL</i>, <i>PHEX</i>, <i>RUNX2</i>, <i>ENPP1</i>, <i>PHOSPHO1</i>, <i>PTH1R</i>, <i>COL11A1</i>, <i>COL24A1</i>, <i>COL22A1</i>, and <i>COL13A1</i>) using cytoHubba of Cytoscape. We also found high gene expression for collagen formation, degradation, absorption, cell-signaling peptides, and bone regulation processes through Gene Ontology (GO) enrichment analysis.</p>","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":"81-95"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10906979/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42542313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comprehensive Review on the Role of Human Epidermal Growth Factor Receptor 2 (HER2) as a Biomarker in Extra-Mammary and Extra-Gastric Cancers","authors":"Fnu Amisha, Paras Malik, P. Saluja, Nitesh Gautam, T. Patel, A. Roy, Sunny R. K. Singh, S. Malapati","doi":"10.3390/onco3020008","DOIUrl":"https://doi.org/10.3390/onco3020008","url":null,"abstract":"The human epidermal growth factor receptors (HERs) are expressed abundantly in the human body. The tumorigenic potential of HER2/neu is linked to its overexpression, amplification or somatic mutation. The HER2 gene amplification leading to protein overexpression has been reported in 25–30% of breast cancers and 10–30% of gastric/gastroesophageal cancers. While HER2 is a well-documented predictive, prognostic, and therapeutic marker in breast and gastric/gastroesophageal cancers, its relevance has also been demonstrated in multiple other malignancies. In this article, we will conduct an extensive review of current data pertaining to HER2 amplification, overexpression, or mutation in cancers other than breast and gastric cancers.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46697215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT Radiomics and Clinical Feature Model to Predict Lymph Node Metastases in Early-Stage Testicular Cancer","authors":"C. Lisson, Sabitha Manoj, Daniel Wolf, Jasper Schrader, S. Schmidt, Meinrad Beer, Michael Goetz, F. Zengerling, C. Lisson","doi":"10.3390/onco3020006","DOIUrl":"https://doi.org/10.3390/onco3020006","url":null,"abstract":"Accurate retroperitoneal lymph node metastasis (LNM) prediction in early-stage testicular germ cell tumours (TGCTs) harbours the potential to significantly reduce over- or undertreatment and treatment-related morbidity in this group of young patients as an important survivorship imperative. We investigated the role of computed tomography (CT) radiomics models integrating clinical predictors for the individualised prediction of LNM in early-stage TGCT. Ninety-one patients with surgically proven testicular germ cell tumours and contrast-enhanced CT were included in this retrospective study. Dedicated radiomics software was used to segment 273 retroperitoneal lymph nodes and extract features. After feature selection, radiomics-based machine learning models were developed to predict LN metastasis. The robustness of the procedure was controlled by 10-fold cross-validation. Using multivariable logistic regression modelling, we developed three prediction models: a radiomics-only model, a clinical-only model, and a combined radiomics–clinical model. The models’ performances were evaluated using the area under the receiver operating characteristic curve (AUC). Finally, decision curve analysis was performed to estimate the clinical usefulness of the predictive model. The radiomics-only model for predicting lymph node metastasis reached a greater discrimination power than the clinical-only model, with an AUC of 0.87 (±0.04; 95% CI) vs. 0.75 (±0.08; 95% CI) in our study cohort. The combined model integrating clinical risk factors and selected radiomics features outperformed the clinical-only and the radiomics-only prediction models, and showed good discrimination with an area under the curve of 0.89 (±0.03; 95% CI). The decision curve analysis demonstrated the clinical usefulness of our proposed combined model. The presented combined CT-based radiomics–clinical model represents an exciting non-invasive tool for individualised LN metastasis prediction in testicular germ cell tumours. Multi-centre validation is required to generate high-quality evidence for its clinical application.","PeriodicalId":74339,"journal":{"name":"Onco","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41607393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Chart Diagnostic System Improves the Diagnostic Accuracy of Cervical Lymph Node Metastasis in Oral Squamous Cell Carcinoma","authors":"Ayako Nomura, T. Ishida, Hiroshi Hijioka, Takuya Yoshimura, Hajime Suzuki, Eturo Nozoe, N. Nakamura","doi":"10.3390/onco3010005","DOIUrl":"https://doi.org/10.3390/onco3010005","url":null,"abstract":"Purpose: To establish a diagnosis method based on imaging findings and histopathological factors associated with cervical lymph node metastasis. Methods: A total of 1587 cervical lymph nodes that were detected using imaging tools in 73 OSCC patients who underwent surgical treatment were enrolled to evaluate the association between imaging findings (long diameter, short diameter, long–short ratio, US findings (hilum and internal echo), contrast effect with enhanced CT, standardized uptake value (SUV) max and SUV average with 18F FDG-Positron Emission Tomography (PET)) and metastatic cervical lymph nodes. In 57 OSCC patients, biopsy specimens were evaluated for histopathologic factors (budding score, lymphatic invasion, vascular invasion, nerve invasion, and YK classification) and the presence of cervical lymph node metastases. Cervical lymph node metastasis was determined based on histopathological examination of the lymph nodes of patients with no metastasis observed 3 years after primary surgery. Results: In total, 22 of the 73 patients had cervical lymph node metastasis pathologically. In the comparison of the presence of metastatic lymph nodes, univariate analysis showed significant differences in cervical lymph node long and short diameter, long/short ratio, internal echo, rim enhancement, SUV max, SUV average, budding score, and vascular invasion. Multivariable analysis showed significant differences in internal echo, rim enhancement, SUV max, and budding score. Conclusions: We propose a chart diagnostic system that combines imaging and histopathological findings to improve the diagnosis of cervical lymph node metastasis.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43214685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fractionated Volumetric Modulated Arc Therapy (FVMAT) for Oligometastatic Brain Tumor","authors":"C. Yeh, Peng-An Lai, Fang-Hui Liu, Chin-Chiao He","doi":"10.3390/onco3010004","DOIUrl":"https://doi.org/10.3390/onco3010004","url":null,"abstract":"Intracranial metastasis is very common in adult cancer patients with an overall incidence of approximately 10–40%. The most common primary tumors responsible for this in adults are lung and breast cancer. Brain metastasis signifies a grave prognosis, with a median survival of 6 to 12 months. They are traditionally managed with palliative care and whole brain radiotherapy (WBRT). WBRT was an effective method to control brain metastases, decreasing corticosteroid use to control tumor-associated edema, and potentially improving overall survival; however, WBRT was found to be associated with a serious neurocognitive degeneration, this adverse effect (AE) follows a biphasic pattern beginning with a transient decline in mental functioning at around 4 months post-treatment, slowly leading to an irreversible neurologic impairment from months to years later. Evidence supports that WBRT can cause radiation injury to the hippocampus, which in turn will lead to a decline in neurocognitive function (NCF). Volumetric modulated arc therapy (VMAT) is a relatively new type of image-guided radiotherapy that treats multiple brain metastasis simultaneously and efficiently with less neurocognitive sequelae. Eighteen cancer patients with limited (≤5 brain tumors) or oligometastatic brain tumor were treated with a spatially fractionated VMAT technique for a total dose of 30 Gy in 10 fractions, the patients tolerated the VMAT treatment with no radiation-induced neurologic toxicities after a mean follow-up of 1 year. Local control rate was 84%, and the median survival for these 19 patients was 11.3 months (range: 9.1–22.4 months). In conclusion, the VMAT is a suitable technique that is a safe and effective treatment for brain oligometastases.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42322647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk Factors and Prevention of Gastric Cancer Development—What Do We Know and What Can We Do?","authors":"Paulina Helisz, Weronika Gwioździk, Karolina Krupa-Kotara, M. Grajek, J. Głogowska-Ligus, J. Słowiński","doi":"10.3390/onco3010003","DOIUrl":"https://doi.org/10.3390/onco3010003","url":null,"abstract":"Gastric cancer (GC) is one of the most common causes of cancer-related deaths. Gastric tumors show a high aggressiveness, which, in turn, contributes to a low survival rate of fewer than 12 months. Considering the above, it was decided to review the current scientific studies that indicate the potential prevention of gastric cancer and clarify the relationship between gastric cancer and the composition of the microorganisms inhabiting the human body. Accordingly, a review paper was prepared based on 97 scientific sources from 2011 to 2022. Particular attention was paid to the most recent scientific studies from the last five years, which account for more than 80% of the cited sources. Taking care of one’s overall health, including undertaking treatment for Helicobacter pylori infection, and following a diet high in anti-inflammatory and immunomodulatory ingredients are the most important factors in reducing the risk of developing gastric cancer.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47051739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regulation of Epithelial–Mesenchymal Transition Pathway and Artificial Intelligence-Based Modeling for Pathway Activity Prediction","authors":"Shihori Tanabe, Sabina Quader, Ryuichi Ono, Horacio Cabral, Kazuhiko Aoyagi, Akihiko Hirose, Edward J. Perkins, Hiroshi Yokozaki, Hiroki Sasaki","doi":"10.3390/onco3010002","DOIUrl":"https://doi.org/10.3390/onco3010002","url":null,"abstract":"Because activity of the epithelial–mesenchymal transition (EMT) is involved in anti-cancer drug resistance, cancer malignancy, and shares some characteristics with cancer stem cells (CSCs), we used artificial intelligence (AI) modeling to identify the cancer-related activity of the EMT-related pathway in datasets of gene expression. We generated images of gene expression overlayed onto molecular pathways with Ingenuity Pathway Analysis (IPA). A dataset of 50 activated and 50 inactivated pathway images of EMT regulation in the development pathway was then modeled by the DataRobot Automated Machine Learning platform. The most accurate models were based on the Elastic-Net Classifier algorithm. The model was validated with 10 additional activated and 10 additional inactivated pathway images. The generated models had false-positive and false-negative results. These images had significant features of opposite labels, and the original data were related to Parkinson’s disease. This approach reliably identified cancer phenotypes and treatments where EMT regulation in the development pathway was activated or inactivated thereby identifying conditions where therapeutics might be applied or developed. As there are a wide variety of cancer phenotypes and CSC targets that provide novel insights into the mechanism of CSCs’ drug resistance and cancer metastasis, our approach holds promise for modeling and simulating cellular phenotype transition, as well as predicting molecular-induced responses.","PeriodicalId":74339,"journal":{"name":"Onco","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135276442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review of Template-Based Neuroimaging Tools in Neuro-Oncology: Novel Insights","authors":"J. Germann, Andrew Yang, Clement Chow, Brendan Santyr, N. Samuel, Artur Vetkas, C. Sarica, G. Elias, M. Voisin, W. Kucharczyk, G. Zadeh, A. Lozano, A. Boutet","doi":"10.3390/onco3010001","DOIUrl":"https://doi.org/10.3390/onco3010001","url":null,"abstract":"Background: A common MRI reference space allows for easy communication of findings, and has led to high-impact discoveries in neuroscience. Brain MRI of neuro-oncology patients with mass lesions or surgical cavities can now be accurately transformed into reference space, allowing for a reliable comparison across patients. Despite this, it is currently seldom used in neuro-oncology, leaving analytic tools untapped. The aim of this study was to systematically review the neuro-oncology literature utilizing reference space. Methods: A systematic review of the neuro-oncology publications was conducted according to PRISMA statement guidelines. Studies specially reporting the use of the Montreal Neurological Institute (MNI) reference space were included. Studies were categorized according to their type of input data and their contributions to the field. A sub-analysis focusing on connectomics and transcriptomics was also included. Results: We identified only 101 articles that utilized the MNI brain in neuro-oncology research. Tumor locations (n = 77) and direct electrocortical stimulation (n = 19) were the most common source of data. A majority of studies (n = 51) provided insights on clinical factors such as tumor subtype, growth progression, and prognosis. A small group of studies (n = 21) have used the novel connectomic and transcriptomic tools. Conclusions: Brain MRI of neuro-oncology patients can be accurately transformed to MNI space. This has contributed to enhance our understanding of a wide variety of clinical questions ranging from tumor subtyping to symptom mapping. Many advanced tools such as connectomics and transcriptomics remain relatively untapped, thereby hindering our knowledge of neuro-oncology.","PeriodicalId":74339,"journal":{"name":"Onco","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46766320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gene Screening in High-Throughput Right-Censored Lung Cancer Data.","authors":"Chenlu Ke,&nbsp;Dipankar Bandyopadhyay,&nbsp;Mario Acunzo,&nbsp;Robert Winn","doi":"10.3390/onco2040017","DOIUrl":"https://doi.org/10.3390/onco2040017","url":null,"abstract":"<p><strong>Background: </strong>Advances in sequencing technologies have allowed collection of massive genome-wide information that substantially advances lung cancer diagnosis and prognosis. Identifying influential markers for clinical endpoints of interest has been an indispensable and critical component of the statistical analysis pipeline. However, classical variable selection methods are not feasible or reliable for high-throughput genetic data. Our objective is to propose a model-free gene screening procedure for high-throughput right-censored data, and to develop a predictive gene signature for lung squamous cell carcinoma (LUSC) with the proposed procedure.</p><p><strong>Methods: </strong>A gene screening procedure was developed based on a recently proposed independence measure. The Cancer Genome Atlas (TCGA) data on LUSC was then studied. The screening procedure was conducted to narrow down the set of influential genes to 378 candidates. A penalized Cox model was then fitted to the reduced set, which further identified a 6-gene signature for LUSC prognosis. The 6-gene signature was validated on datasets from the Gene Expression Omnibus.</p><p><strong>Results: </strong>Both model-fitting and validation results reveal that our method selected influential genes that lead to biologically sensible findings as well as better predictive performance, compared to existing alternatives. According to our multivariable Cox regression analysis, the 6-gene signature was indeed a significant prognostic factor (<i>p</i>-value < 0.001) while controlling for clinical covariates.</p><p><strong>Conclusions: </strong>Gene screening as a fast dimension reduction technique plays an important role in analyzing high-throughput data. The main contribution of this paper is to introduce a fundamental yet pragmatic model-free gene screening approach that aids statistical analysis of right-censored cancer data, and provide a lateral comparison with other available methods in the context of LUSC.</p>","PeriodicalId":74339,"journal":{"name":"Onco","volume":"2 4","pages":"305-318"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10100230/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9323816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}