Sequence Fusion Algorithm of Tumor Gene Sequencing and Alignment Based on Machine Learning

With the rapid development of DNA high-throughput testing technology, there is a high correlation between DNA sequence variation and human diseases, and detecting whether there is variation in DNA sequence has become a hot research topic at present. DNA sequence variation is relatively rare, and the establishment of DNA sequence sparse matrix, which can quickly detect and reason fusion variation point, has become an important work of tumor gene testing. Because there are differences between the current comparison software and mutation detection software in detecting the same sample, there are errors between the results of derivative sequence comparison and the detection of mutation. In this paper, SNP and InDel detection methods based on machine learning and sparse matrix detection are proposed, and VarScan 2, Genome Analysis Toolkit (GATK), BCFtools, and FreeBayes are compared. In the research of SNP and InDel detection with intelligent reasoning, the experimental results show that the detection accuracy and recall rate are better when the depth is increasing. The reasoning fusion method proposed in this paper has certain advantages in comparison effect and discovery in SNP and InDel and has good effect on swelling and pain gene detection.

Study on Apoptosis of Prostate Cancer Cells Induced by IκBα Overexpression Synergistic with Poly (Lactic-Co-Glycolic Acid)-Curcumin Nanoparticles

Objective. To investigate the synergistic effects of IκBα overexpression and poly (lactic-co-glycolic acid)-curcumin nanoparticles (PLGA-Cur-NPs) on prostate cancer (PC) and reveal the underlying mechanisms of cooperative sensitization induced by curcumin. Methods. Proliferation and apoptosis rate in IκBα overexpressed and PLGA-Cur-NPs-treated PC cells were detected by MTT and flow cytometry assay. The expression levels of IκBα, apoptosis-related, and signaling proteins were measured by western blotting assay. Results. PC cell proliferation was significantly inhibited by the overexpression of IκBα. The apoptosis rate of PC cells was significantly increased at a high concentration of curcumin exposure, while the activation of NF-κB pathway was obviously inhibited. In addition, PLGA-Cur-NPs treatment synergistic with IκBα overexpression enhanced the apoptosis of PC cells by suppressing the NF-κB pathway activation. Conclusion. IκBα overexpression synergistic with PLGA-Cur-NPs could obviously inhibit proliferation, induce apoptosis, and suppress the activation of NF-κB pathway in PC cells. These findings may provide an experimental basis to establish the tumor gene therapy combined with traditional Chinese medicine treatment, thus promoting the clinical application of both tumor gene therapy and anti-tumor Chinese medicine.

Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network

Background Although great efforts have been made to study the occurrence and development of glioma, the molecular mechanisms of glioma are still unclear. Single-cell sequencing technology provides a new perspective for researchers to explore the pathogens of tumors to further help make treatment and prognosis decisions for patients with tumors. Methods In this study, we proposed an algorithm framework to explore the molecular mechanisms of glioma by integrating single-cell gene expression profiles and gene regulatory relations. First, since there were great differences among malignant cells from different glioma samples, we analyzed the expression status of malignant cells for each sample, and then tumor consensus genes were identified by constructing and analyzing cell-specific networks. Second, to comprehensively analyze the characteristics of glioma, we integrated transcriptional regulatory relationships and consensus genes to construct a tumor-specific regulatory network. Third, we performed a hybrid clustering analysis to identify glioma cell types. Finally, candidate tumor gene biomarkers were identified based on cell types and known glioma-related genes. Results We got six identified cell types using the method we proposed and for these cell types, we performed functional and biological pathway enrichment analyses. The candidate tumor gene biomarkers were analyzed through survival analysis and verified using literature from PubMed. Conclusions The results showed that these candidate tumor gene biomarkers were closely related to glioma and could provide clues for the diagnosis and prognosis of patients with glioma. In addition, we found that four of the candidate tumor gene biomarkers (NDUFS5, NDUFA1, NDUFA13, and NDUFB8) belong to the NADH ubiquinone oxidoreductase subunit gene family, so we inferred that this gene family may be strongly related to glioma.

Deep Convolutional Neural Networks Detect Tumor Genotype from Pathological Tissue Images in Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GIST) are common mesenchymal tumors, and their effective treatment depends upon the mutational subtype of the KIT/PDGFRA genes. We established deep convolutional neural network (DCNN) models to rapidly predict drug-sensitive mutation subtypes from images of pathological tissue. A total of 5153 pathological images of 365 different GISTs from three different laboratories were collected and divided into training and validation sets. A transfer learning mechanism based on DCNN was used with four different network architectures, to identify cases with drug-sensitive mutations. The accuracy ranged from 87% to 75%. Cross-institutional inconsistency, however, was observed. Using gray-scale images resulted in a 7% drop in accuracy (accuracy 80%, sensitivity 87%, specificity 73%). Using images containing only nuclei (accuracy 81%, sensitivity 87%, specificity 73%) or cytoplasm (accuracy 79%, sensitivity 88%, specificity 67%) produced 6% and 8% drops in accuracy rate, respectively, suggesting buffering effects across subcellular components in DCNN interpretation. The proposed DCNN model successfully inferred cases with drug-sensitive mutations with high accuracy. The contribution of image color and subcellular components was also revealed. These results will help to generate a cheaper and quicker screening method for tumor gene testing.

The relevance of Chemistry in Tumor microenvironment of Cancer Patient

The prime mechanisms for the alteration or reshaping of common somatic gene cells into malignant tumor gene cells are transgenic or oncogene activation and tumor-suppresser gene cell dismission. Cancer genetic cells are the propulsion of growing and expansion. On the other side, they are incapable of developing them self. The wen microhabitat is thought of plays an extra energetic role in Wen improvement than merely existing as a bystander. Wen Cells dexterously enroll connective tissue cells. Through several walkways, which then supply Wen Cells with improved Signs, median metabolites, and a favorable environment for tumor expansion and metastasis. Lymphoma or tumor cells and the microhabitat environment work both will promote large expansion and metathetical potential through mutual communication. Understanding the play of the wen or tumor sensitive small environment in Wen Expansion can direct to new routes to target the Wen Small environment for more efficient anti-tumor medications or cures. In this study, we address the methods involved in Wen or tumor cells enrolling connective cells to the prime tumor place. Along with that it also explained and highlighted the small microhabitats environment and tumor development process. We also mentioned some of the possible potential treatment approaches of cancer treatment which can mighty be helpful for better results.

Lipoic Acid-Modified Oligoethyleneimine-Mediated miR-34a Delivery to Achieve the Anti-Tumor Efficacy

MiR-34a, an important tumor suppressor, has been demonstrated to possess great potential in tumor gene therapy. To achieve the upregulation of miR-34a expression level, an oligoethyleneimine (OEI) derivative was constructed and employed as the carrier through the modification with lipoic acid (LA), namely LA-OEI. In contrast to OEI, the derivative LA-OEI exhibited superior transfection efficiency measured by confocal laser scanning microscopy and flow cytometry, owing to rapid cargo release in the disulfide bond-based reduction sensitive pattern. The anti-proliferation and anti-migration effects were tested after the miR-34a transfection to evaluate the anti-tumor response, using human cervical carcinoma cell line HeLa as a model. The delivery of LA-OEI/miR-34a nanoparticles could achieve obvious anti-proliferative effect caused by the induction of cell apoptosis and cell cycle arrest at G1 phase. In addition, it could inhibit the migration of tumor cells via the downregulation of MMP-9 and Notch-1 level. Overall, the LA-OEI-mediated miR-34a delivery was potential to be used as an effective way in the tumor gene therapy.

Molecular Tests and Target Therapies in Oncology: recommendations from the Italian workshop

Next-generation sequencing (NGS) and liquid biopsy are new technologies that can allow overall tumor profiling in a single analysis and play an important role in the implementation of precision oncology. However, the lack of guidelines in this setting has limited the development of precision oncology in Italy. This article summarizes recommendations for the appropriate use of NGS in tumor gene profiling, as well as access to tests and target drugs, that were prepared by a group of key opinion leaders and relevant stakeholders. In particular, the need to create laboratory networks capable of carrying out NGS tests in Italy is highlighted. It also appears necessary to establish an adequate reimbursement system for NGS tests. However, the expert panel recommends that the use of NGS tests in clinical practice should be limited to specific tumor types, based on the number and complexity of biomarkers and the availability of treatments.

Distinct difference in tumor-infiltrating immune cells between Wilms' tumor gene 1 peptide vaccine and anti-programmed cell death-1 antibody therapies

Backgrounds Wilms’ tumor gene 1 (WT1) peptide vaccine and anti-programmed cell death-1 (PD-1) antibody are expected as immunotherapies to improve the clinical outcome of glioblastoma. The aims of this study were to clarify how each immunotherapy affect tumor-infiltrating immune cells (TIIs) and to determine whether the combination of these two therapies could synergistically work. Methods Mice were transplanted with WT1 and programed cell death-ligand 1 (PD-L1) doubly expressing glioblastoma cells into brain followed by treatment with WT1 peptide vaccine, anti-PD-1 antibody, or the combination of the two, and survival of each therapy was compared. CD45 + cells were positively selected as TIIs from the brains with tumors, and TIIs were compared between WT1 peptide vaccine and anti-PD-1 antibody therapies. Results Most mice seemed to be cured by the combination therapy with WT1 peptide vaccine and anti-PD-1 antibody, which was much better survival than each monotherapy. A large number of CD4 + T cells, CD8 + T cells, NK cells including WT1-specific CD8 + and CD4 + T cells infiltrated into the glioblastoma in WT1 peptide vaccine-treated mice. On the other hand, the number of TIIs did not increase, but instead PD-1 molecule expression was decreased on the majority of the tumor-infiltrating CD8 + T cells in the anti-PD-1 antibody-treated mice. Conclusion Our results clearly demonstrated that WT1 peptide vaccine and anti-PD-1 antibody therapies worked in the different steps of cancer-immunity cycle and that the combination of the two therapies could work synergistically against glioblastoma.