Current Insights on Neoplasms and Adequate Dental Care for Patients with Oral Cancer / Actualización sobre Neoplasmas y su Correcta Atención Odontológica en Pacientes con Cancer Oral

The present study aimed to review the literature on the main complications of antineoplastic therapies and the degree of knowledge of dental surgeons about these complications. A bibliographic search was conducted in the main health databases PUBMED (www.pubmed.gov) and Scholar Google (www.scholar.google.com.br), in which studies published from 1987 to 2023 were collected. Laboratory studies, case reports, systematic and literature reviews, which were developed in living individuals, about the main neoplastic genes and their relationship with the cells of individuals affected by neoplasms in the head and neck region, and studies on the care with this group of patients, were included. Therefore, articles that did not deal with neoplasm and the main complications of antineoplastic therapies were excluded. Neoplasm is a clonal disorder, caused by mutations, resulting from changes in the genetic structure of cells. Each healthy cell has instructions on how to grow and divi de. In the presence of any error in these instructions (mutation), it can result in a diseased cell that, when proliferating, may cause a tumor. Countless knowledge has been accumulated over the years on the main characteristics of neoplasms, whether they are cancer cell biology, carcinogenesis mechanism, neoplasms of the maxillofacial system and sequels of antineoplastic treatments. In this context, methods have been developed that offer a better quality of life for patients diagnosed with this pathology, as well as preventive vaccine models that may, in the not too distant future, contribute to this goal to be successfully achieved.

El presente estudio tuvo como objetivo revisar la literatura sobre las principales complicaciones de las terapias antineoplásicas y el grado de conocimiento de los odontólogos sobre este abordaje. Se realizó una búsqueda bibliográfica en las principales bases de datos de salud PUBMED (www.pubmed.gov) y Scholar Google (www.scholar.google.com.br), en la que se recopilaron estudios publicados entre 1987 y 2023. Fueron incluidos estudios de laboratorio, relatos de casos, revisiones de la literatura y revisiones sistemáticas, desarrolladas en individuos vivos, que incluyeran los principales genes neoplásicos y su relación con las células de individuos afectados por neoplasias en la cabeza y el cuello. También, se tuvieron en cuenta estudios relacionados con la atención a este grupo de pacientes. La neoplasia es un trastorno clonal, causado por mutaciones, como resultado de cambios en la estructura genética de las células. Cada célula sana tiene instrucciones sobre cómo crecer y dividirse. En presencia de cualquier error en estas instrucciones (mutación), puede provocar una célula alterada que, al proliferar, puede causar un tumor. Se han acumulado innumerables conocimientos a lo largo de los años sobre las principales características de las neoplasias, ya sea sobre biología de células cancerosas, el mecanismo de la carcinogénesis, la neoplasias del sistema maxilofacial y las diferentes secuelas de tratamientos antineoplásicos. En este contexto, se han desarrollado métodos que ofrecen una mejor calidad de vida para los pacientes diagnosticados con esta patología, así como modelos de vacunas preventivas que, en un futuro no muy lejano, pueden contribuir a alcanzar este objetivo con éxito.

Epigenetic study of early breast cancer (EBC) based on DNA methylation and gene integration analysis.

Breast cancer (BC) is one of the leading causes of cancer-related deaths in women. The purpose of this study is to identify key molecular markers related to the diagnosis and prognosis of early breast cancer (EBC). The data of mRNA, lncRNA and DNA methylation were downloaded from The Cancer Genome Atlas (TCGA) dataset for identification of differentially expressed mRNAs (DEmRNAs), differentially expressed lncRNAs (DElncRNAs) and DNA methylation analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyzes were used to identify the biological functions of DEmRNAs. The correlation analysis between DNA methylation and DEmRNAs was carried out. Then, diagnostic analysis and prognostic analysis of identified DEmRNAs and DElncRNAs were also performed in the TCGA database. Subsequently, methylation state verification for identified DEmRNAs was performed in the GSE32393 dataset. In addition, real-time polymerase chain reaction (RT-PCR) in vitro verification of genes was performed. Finally, AC093110.1 was overexpressed in human BC cell line MCF-7 to verify cell proliferation and migration. In this study, a total of 1633 DEmRNAs, 750 DElncRNAs and 8042 differentially methylated sites were obtained, respectively. In the Venn analysis, 11 keys DEmRNAs (ALDH1L1, SPTBN1, MRGPRF, CAV2, HSPB6, PITX1, WDR86, PENK, CACNA1H, ALDH1A2 and MME) were we found. ALDH1A2, ALDH1L1, HSPB6, MME, MRGPRF, PENK, PITX1, SPTBN1, WDR86 and CAV2 may be considered as potential diagnostic gene biomarkers in EBC. Strikingly, CAV2, MME, AC093110.1 and AC120498.6 were significantly actively correlated with survival. Methylation state of identified DEmRNAs in GSE32393 dataset was consistent with the result in TCGA. AC093110.1 can affect the proliferation and migration of MCF-7. ALDH1A2, ALDH1L1, HSPB6, MME, MRGPRF, PENK, PITX1, SPTBN1, WDR86 and CAV2 may be potential diagnostic gene biomarkers of EBC. Strikingly, CAV2, MME, AC093110.1 and AC120498.6 were significantly actively correlated with survival. The identification of these genes can help in the early diagnosis and treatment of EBC. In addition, AC093110.1 can regulate SPTBN1 expression and play an important role in cell proliferation and migration, which provides clues to clarify the regulatory mechanism of EBC.

Gene-Level Germline Contributions to Clinical Risk of Recurrence Scores in Black and White Patients with Breast Cancer.

Continuous risk of recurrence scores (CRS) based on tumor gene expression are vital prognostic tools for breast cancer. Studies have shown that Black women (BW) have higher CRS than White women (WW). Although systemic injustices contribute substantially to breast cancer disparities, evidence of biological and germline contributions is emerging. In this study, we investigated germline genetic associations with CRS and CRS disparity using approaches modeled after transcriptome-wide association studies (TWAS). In the Carolina Breast Cancer Study, using race-specific predictive models of tumor expression from germline genetics, we performed race-stratified (N = 1,043 WW, 1,083 BW) linear regressions of three CRS (ROR-S: PAM50 subtype score; proliferation score; ROR-P: ROR-S plus proliferation score) on imputed tumor genetically regulated tumor expression (GReX). Bayesian multivariate regression and adaptive shrinkage tested GReX-prioritized genes for associations with tumor PAM50 expression and subtype to elucidate patterns of germline regulation underlying GReX-CRS associations. At FDR-adjusted P < 0.10, 7 and 1 GReX prioritized genes among WW and BW, respectively. Among WW, CRS were positively associated with MCM10, FAM64A, CCNB2, and MMP1 GReX and negatively associated with VAV3, PCSK6, and GNG11 GReX. Among BW, higher MMP1 GReX predicted lower proliferation score and ROR-P. GReX-prioritized gene and PAM50 tumor expression associations highlighted potential mechanisms for GReX-prioritized gene to CRS associations. Among patients with breast cancer, differential germline associations with CRS were found by race, underscoring the need for larger, diverse datasets in molecular studies of breast cancer. These findings also suggest possible germline trans-regulation of PAM50 tumor expression, with potential implications for CRS interpretation in clinical settings. SIGNIFICANCE: This study identifies race-specific genetic associations with breast cancer risk of recurrence scores and suggests mediation of these associations by PAM50 subtype and expression, with implications for clinical interpretation of these scores.

Construction of a Pearson- and MIC-Based Co-expression Network to Identify Potential Cancer Genes.

The weighted gene co-expression network analysis (WGCNA) method constructs co-expressed gene modules based on the linear similarity between paired gene expressions. Linear correlations are the main form of similarity between genes, however, nonlinear correlations still existed and had always been ignored. We proposed a modified network analysis method, WGCNA-P + M, which combines Pearson's correlation coefficient and the maximum information coefficient (MIC) as the similarity measures to assess the linear and nonlinear correlations between genes, respectively. Taking two real datasets, GSE44861 and liver hepatocellular carcinoma (TCGA-LIHC), as examples, we compared the gene modules constructed by WGCNA-P + M and WGCNA from four perspectives: the "Usefulness" score, GO enrichment analysis on genes in the gray module, prediction performance of the top hub gene, survival analysis and literature reports on different hub genes. The results showed that the modules obtained by WGCNA-P + M are more biological meaningful, the hub genes obtained from WGCNA-P + M have more potential cancer genes.

Mucosal melanomas of different anatomic sites share a common global DNA methylation profile with cutaneous melanoma but show location-dependent patterns of genetic and epigenetic alterations.

Cutaneous, ocular, and mucosal melanomas are histologically indistinguishable tumors that are driven by a different spectrum of genetic alterations. With current methods, identification of the site of origin of a melanoma metastasis is challenging. DNA methylation profiling has shown promise for the identification of the site of tumor origin in various settings. Here we explore the DNA methylation landscape of melanomas from different sites and analyze if different melanoma origins can be distinguished by their epigenetic profile. We performed DNA methylation analysis, next generation DNA panel sequencing, and copy number analysis of 82 non-cutaneous and 25 cutaneous melanoma samples. We further analyzed eight normal melanocyte cell culture preparations. DNA methylation analysis separated uveal melanomas from melanomas of other primary sites. Mucosal, conjunctival, and cutaneous melanomas shared a common global DNA methylation profile. Still, we observed location-dependent DNA methylation differences in cancer-related genes, such as low frequencies of RARB (7/63) and CDKN2A promoter methylation (6/63) in mucosal melanomas, or a high frequency of APC promoter methylation in conjunctival melanomas (6/9). Furthermore, all investigated melanomas of the paranasal sinus showed loss of PTEN expression (9/9), mainly caused by promoter methylation. This was less frequently seen in melanomas of other sites (24/98). Copy number analysis revealed recurrent amplifications in mucosal melanomas, including chromosomes 4q, 5p, 11q and 12q. Most melanomas of the oral cavity showed gains of chromosome 5p with TERT amplification (8/10), while 11q amplifications were enriched in melanomas of the nasal cavity (7/16). In summary, mucosal, conjunctival, and cutaneous melanomas show a surprisingly similar global DNA methylation profile and identification of the site of origin by DNA methylation testing is likely not feasible. Still, our study demonstrates tumor location-dependent differences of promoter methylation frequencies in specific cancer-related genes together with tumor site-specific enrichment for specific chromosomal changes and genetic mutations. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Effect of HDAC9 inhibition on epithelial-mesenchymal transition in CD133+ prostate cancer cell lines.

A small fraction of cancer cells known as cancer stem cells (CSCs) are considered to give rise to differentiated cancer cells and have been proposed to predict cancer recurrence and metastasis. There is further evidence that CSCs may act as metastatic precursors of epithelial-mesenchymal transition (EMT). In the present study, we investigated the key molecules involved in maintaining the stability of CSCs by inducing ectopic overexpression of CD133 to characterize EMT in human prostate cancer cell lines, including PC-3, DU145, and LnCaP cells. Additionally, we investigated whether a specific inhibitor of concomitantly expressed metastasis-related genes could alleviate EMT properties in CD133-overexpressing prostate cancer cells. Ectopic overexpression of CD133 in PC-3, DU145, and LnCaP cells led to an increase in the expression of HDAC9. Moreover, HDAC9 inhibition led to a decrease in EMT properties along with increased E-cadherin expression, a narrower wound gap distance, and enhanced cell invasiveness through the suppression of ß-catenin activation and its translocation to the nucleus. Overall, these results suggest that HDAC9 inhibition plays a functional role in the modulation of EMT properties in CSC-like prostate cancer cells. Therefore, these findings could facilitate the development of therapeutic strategies for controlling prostate cancer metastasis.

Ampullary carcinoma of the duodenum: current clinical issues and genomic overview.

Ampullary carcinomas of the duodenum are uncommon. Moreover, the diversity in the clinical outcomes of these patients makes it difficult to interpret previous studies and clinical trial results. The difficulty in proper staging of ampullary carcinomas, especially with regard to the T category of the tumor in the TNM system, reflects the anatomic complexity and non-uniform histopathologic subtypes. One major reason for this difficulty in interpretation is that the tumors may arise from any of the three epithelia (duodenal, biliary, or pancreatic) that converge at this location. Generally, ampullary carcinomas are classified into intestinal and pancreaticobiliary types based on morphology and immunohistochemical features. While many studies have described their specific characteristics and clinical impact, the prognostic value of these subtypes is controversial. In recent years, whole-exome sequencing analyses have advanced our understanding of the genomic overview of ampullary carcinoma. Gene mutations serve as prognostic and predictive biomarkers for this disease. Therefore, basic knowledge of the genomic profile of ampullary carcinomas is required for surgeons to understand how best to apply precision medicine as well as surgery and adjuvant therapies. This review provides an overview of the current basic and clinical issues of ampullary carcinoma.

An integrative pan-cancer analysis reveals the oncogenic role of mutS homolog 6 (MSH6) in human tumors.

There are three most important mismatch repair genes in the mismatch repair system, MSH6 is one of them and it plays an essential role in DNA mismatch repair. Several emerging cell- or animal-based studies have verified that MSH6 mutations are closely linked to the occurrence, progression or metastasis of cancer, but there is still no practicable pan-cancer analysis. On account of the available datasets of the cancer genome atlas (TCGA) and Gene expression omnibus (GEO), a comprehensive analysis of the potential carcinogenic effects of the MSH6 gene was conducted in 33 human cancers. MSH6 was highly expressed in most cancers, and the high expression of MSH6 was associated with poor overall survival prognosis of patients with multiple cancers, such as adrenocortical carcinoma. MSH6 mutations occurred in most cancers and were closely related to the prognosis of cancer patients. Increased phosphorylation levels of S227 and S830 were noted in several tumors, including breast cancer and colon cancer. MSH6 expression was also observed to be correlated with cancer-associated fibroblasts and CD8+ T-cells infiltration levels in various cancer types, e. g. pancreatic adenocarcinoma or testicular germ cell tumors. Furthermore, pathway enrichment analysis demonstrated that the main biological activities of MSH6 were related to ATPase activity, mismatch repair, and DNA metabolism-related functions. Altogether, our pan-cancer research has suggested that the MSH6 expression level was closely related to the carcinogenesis and prognosis of certain tumors, which helps to know the effect of MSH6 in tumorigenesis from the point of view of clinical tumor samples.

DNM1: A Prognostic Biomarker Associated with Immune Infiltration in Colon Cancer-A Study Based on TCGA Database.

AIM: The aim of our work was to determine the utility of DNM1 as a biomarker for the diagnosis and prognosis of colon cancer (CC). METHODS: DNM1 expression variations in CC vs. normal tissues were investigated using The Cancer Genome Atlas (TCGA) database. The association of DNM1 expression levels with the clinicopathological variables in CC prognosis was investigated using logistic regression analyses. Independent prognostic factors for CC were evaluated using univariate and multivariate Cox regression analyses. The correlation between DNM1 expression and immune cell infiltration was estimated using single-sample Gene Set Enrichment Analysis (ssGSEA). RESULTS: DNM1 expression in CC tissues was significantly higher than that in normal tissues. High DNM1 expression was significantly correlated with M stage, N stage, perineural invasion and lymphatic invasion and predicted poor prognosis. The univariate analysis highlighted that DNM1 was an independent CC risk factor. Results of ssGSEA showed that DNM1 was linked to several cancer-related pathways, including the neuroactive ligand-receptor interaction, hypertrophic cardiomyopathy, ECM-receptor interaction, dilated cardiomyopathy, and calcium signaling pathway. Moreover, DNM1 expression was positively correlated with the level of infiltration by Neutrophils, Tregs, NK cells, and Macrophages. CONCLUSION: DNM1 has a significant function and has diagnostic and prognostic potential for CC.

Landscape of the oncogenic role of fatty acid synthase in human tumors.

BACKGROUND: Identifying a unique and common regulatory pathway that drives tumorigenesis in cancers is crucial to foster the development of effective treatments. However, a systematic analysis of fatty acid synthase across pan-cancers has not been carried out. METHODS: We investigated the oncogenic roles of fatty acid synthase in 33 cancers based on the cancer genome atlas and gene expression omnibus. RESULTS: Fatty acid synthase is profoundly expressed in most cancers and is an important factor in predicting the outcome of cancer patients. Further, the level of S207 phosphorylation was found to be improved in several neoplasms (e.g., colon cancer). Fatty acid synthase expression is related to tumor-infiltrating immune cells in tumors (e.g., CD8+ T-cell infiltration level in cervical squamous cell carcinoma). Moreover, hormone receptor binding- and fatty acid metabolic process-associated pathways are involved in the functional mechanisms of fatty acid synthase. CONCLUSIONS: This study provides a complete understanding of the oncogenic role of fatty acid synthase in human tumors.

Precise Characterization of Genetic Interactions in Cancer via Molecular Network Refining Processes.

Genetic interactions (GIs), such as the synthetic lethal interaction, are promising therapeutic targets in precision medicine. However, despite extensive efforts to characterize GIs by large-scale perturbation screening, considerable false positives have been reported in multiple studies. We propose a new computational approach for improved precision in GI identification by applying constraints that consider actual biological phenomena. In this study, GIs were characterized by assessing mutation, loss of function, and expression profiles in the DEPMAP database. The expression profiles were used to exclude loss-of-function data for nonexpressed genes in GI characterization. More importantly, the characterized GIs were refined based on Kyoto Encyclopedia of Genes and Genomes (KEGG) or protein-protein interaction (PPI) networks, under the assumption that genes genetically interacting with a certain mutated gene are adjacent in the networks. As a result, the initial GIs characterized with CRISPR and RNAi screenings were refined to 65 and 23 GIs based on KEGG networks and to 183 and 142 GIs based on PPI networks. The evaluation of refined GIs showed improved precision with respect to known synthetic lethal interactions. The refining process also yielded a synthetic partner network (SPN) for each mutated gene, which provides insight into therapeutic strategies for the mutated genes; specifically, exploring the SPN of mutated BRAF revealed ELAVL1 as a potential target for treating BRAF-mutated cancer, as validated by previous research. We expect that this work will advance cancer therapeutic research.

Identification of key genes in osteosarcoma - before and after CDK7 treatment.

BACKGROUND: Osteosarcoma is one of the most common bone tumors, with a high degree of malignancy and a poor prognosis. Recent studies have shown that THZ2, a cyclin-dependent kinase 7 inhibitor, can exhibit strong antibone tumor effects in vivo and in vitro by inhibiting transcriptional activity. In this study, by screening the differentially expressed genes (DEGs) of osteosarcoma cells before and after THZ2 treatment, it provides new possible targets for the future targeted therapy of osteosarcoma. METHODS: Download the gene expression profile of GSE134603 from the Gene Expression Omnibus database, and use the R software package "limma Geoquery" to screen DEGs. DAVID database was used for gene ontology analysis of DEGs. Use search tool for the retrieval of interacting genes online database and Cytoscape software to construct protein-protein interaction network. Use the "MCODE" plugin in Cytoscape to analyze key molecular complexes (module) of DEGs, and use the "Cluego" plugin to perform Kyoto Encyclopedia of Genes and Genomes enrichment analysis on module genes. The Hub gene is selected from the genes in DEGs that coexist in the top 30 Degree and the Kyoto Encyclopedia of Genes and Genomes pathway. RESULTS: A total of 1033 DEGs were screened, including 800 up-regulated genes and 233 down-regulated genes. Gene ontology analysis showed that cell component is the main enrichment area of DEGs, mainly in the nucleus, cytoplasm, and nucleoplasm. In addition, in molecular function analysis, DEGs are mainly enriched in the process of protein binding. In biological process analysis, changes in DEGs can also be observed in transcription and regulation using DNA as a template. Twenty-nine module genes are enriched in the Ribosome biogenesis in eukaryotes pathway. Finally, 4 key genes are drawn: essential for mitotic growth 1, U3 SnoRNP protein 3 homolog, U3 small nucleolar RNA-associated protein 15 homolog, and WD repeat domain 3. CONCLUSION: This study found that the 4 genes essential for mitotic growth 1, U3 SnoRNP protein 3 homolog, U3 small nucleolar RNA-associated protein 15 homolog, WD repeat domain 3, and the ribosome biogenesis in eukaryotes pathway play a very important role in the occurrence and development of osteosarcoma, and can become a new target for molecular targeted therapy of osteosarcoma in the future.

Development and validation of a novel lipid metabolism-related gene prognostic signature and candidate drugs for patients with bladder cancer.

BACKGROUND: Bladder cancer (BLCA) is a common cancer associated with an unfavorable prognosis. Increasing numbers of studies have demonstrated that lipid metabolism affects the progression and treatment of tumors. Therefore, this study aimed to explore the function and prognostic value of lipid metabolism-related genes in patients with bladder cancer. METHODS: Lipid metabolism-related genes (LRGs) were acquired from the Molecular Signature Database (MSigDB). LRG mRNA expression and patient clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a signature for predicting overall survival of patients with BLCA. Kaplan-Meier analysis was performed to assess prognosis. The connectivity Map (CMAP) database was used to identify small molecule drugs for treatment. A nomogram was constructed and assessed by combining the signature and other clinical factors. The CIBERSORT, MCPcounter, QUANTISEQ, XCELL, CIBERSORT-ABS, TIMER and EPIC algorithms were used to analyze the immunological characteristics. RESULTS: An 11-LRG signature was successfully constructed and validated to predict the prognosis of BLCA patients. Furthermore, we also found that the 11-gene signature was an independent hazardous factor. Functional analysis suggested that the LRGs were closely related to the PPAR signaling pathway, fatty acid metabolism and AMPK signaling pathway. The prognostic model was closely related to immune cell infiltration. Moreover, the expression of key immune checkpoint genes (PD1, CTLA4, PD-L1, LAG3, and HAVCR2) was higher in patients in the high-risk group than in those in the low-risk group. The prognostic signature based on 11-LRGs exhibited better performance in predicting overall survival than conventional clinical characteristics. Five small molecule drugs could be candidate drug treatments for BLCA patients based on the CMAP dataset. CONCLUSIONS: In conclusion, the current study identified a reliable signature based on 11-LRGs for predicting the prognosis and response to immunotherapy in patients with BLCA. Five small molecule drugs were identified for the treatments of BLCA patients.

Molecular alterations in retinoblastoma beyond RB1.

Retinoblastoma is the most common malignant ocular tumor in children. Although RB1 alterations are most frequently involved in the etiology of retinoblastoma, candidate driver events and somatic alterations leading to cell transformation, tumor onset and progression remain poorly understood. In this study, we identified novel genomic alterations in tumors with a panel of 160 genes. Sanger sequencing and Multiplex Ligation-dependent Probe Amplification (MLPA) were initially performed for identifying patients without apparent RB1 alterations in blood DNA. Subsequently, NGS analyses of 24 paired (blood/tumor) samples of these patients were carried out for identifying somatic mutations and copy number variation in RB1 and other 159 genes. One novel pathogenic RB1 mutation and seven novel VUS were identified as well as 90 novel pathogenic mutations in 61 other genes. Twenty-three genes appeared exclusively mutated in tumors without altered RB1 alleles and three frequently affected biological pathways while five other tumors did not show pathogenic RB1 alterations or SNV/indels in 159 other genes. Curiously, deletion of GATA2, AKT1, ARID1A, DNMT3A, MAP2K2, MEN1, MTOR, PTCH1 and SUFU (in homo- or heterozygosity) were exclusively found in these tumors when compared to those with any pathogenic alterations, probably indicating genes that might be essential for the development of retinoblastoma regardless of a functional RB1. Identification of genes associated with retinoblastoma will contribute to understanding presently unknown aspects of this malignancy, which might be essential for its initiation and progression, as well as providing valuable molecular markers.

Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability.

Genetic polymorphisms in DNA damage repair and tumor suppressor genes have been associated with increasing the risk of several types of cancer. Analyses of putative functional single nucleotide polymorphisms (SNP) in such genes can greatly improve human health by guiding choice of therapeutics. In this study, we selected nine genes responsible for various cancer types for gene enrichment analysis and found that BRCA1, ATM, and TP53 were more enriched in connectivity. Therefore, we used different computational algorithms to classify the nonsynonymous SNPs which are deleterious to the structure and/or function of these three proteins. The present study showed that the major pathogenic variants (V1687G and V1736G of BRCA1, I2865T and V2906A of ATM, V216G and L194H of TP53) might have a greater impact on the destabilization of the proteins. To stabilize the high-risk SNPs, we performed mutation site-specific molecular docking analysis and validated using molecular dynamics (MD) simulation and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) studies. Additionally, SNPs of untranslated regions of these genes affecting miRNA binding were characterized. Hence, this study will assist in developing precision medicines for cancer types related to these polymorphisms.

Molecular Alterations in Pediatric Low-Grade Gliomas That Led to Death.

Pediatric low-grade gliomas (PLGGs) have excellent long-term survival, but death can occasionally occur. We reviewed all PLGG-related deaths between 1975 and 2019 at our institution: 48 patients were identified; clinical data and histology were reviewed; targeted exome sequencing was performed on available material. The median age at diagnosis was 5.2 years (0.4-23.4 years), at death was 13.0 years (1.9-43.2 years), and the overall survival was 7.2 years (0.0-33.3 years). Tumors were located throughout CNS, but predominantly in the diencephalon. Diagnoses included low-grade glioma, not otherwise specified (n = 25), pilocytic astrocytoma (n = 15), diffuse astrocytoma (n = 3), ganglioglioma (n = 3), and pilomyxoid astrocytoma (n = 2). Recurrence occurred in 42/48 cases, whereas progression occurred in 10. The cause of death was direct tumor involvement in 31/48 cases. Recurrent drivers included KIAA1549-BRAF (n = 13), BRAF(V600E) (n = 3), NF1 mutation (n = 3), EGFR mutation (n = 3), and FGFR1-TACC1 fusion (n = 2). Single cases were identified with IDH1(R132H), FGFR1(K656E), FGFR1 ITD, FGFR3 gain, PDGFRA amplification, and mismatch repair alteration. CDKN2A/B, CDKN2C, and PTEN loss was recurrent. Patients who received only chemotherapy had worse survival compared with patients who received radiation and chemotherapy. This study demonstrates that PLGG that led to death have diverse molecular characteristics. Location and co-occurring molecular alterations with malignant potential can predict poor outcomes.

Deep learning-based gene selection in comprehensive gene analysis in pancreatic cancer.

The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selection method suitable for gene selection. Our novel deep learning model includes an additional feature-selection layer. After model training, the units in this layer with high weights correspond to the genes that worked effectively in the processing of the networks. Cancer tissue samples and adjacent normal pancreatic tissue samples were collected from 13 patients with pancreatic ductal adenocarcinoma during surgery and subsequently frozen. After processing, gene expression data were extracted from the specimens using RNA sequencing. Task 1 for the model training was to discriminate between cancerous and normal pancreatic tissue in six patients. Task 2 was to discriminate between patients with pancreatic cancer (n = 13) who survived for more than one year after surgery. The most frequently selected genes were ACACB, ADAMTS6, NCAM1, and CADPS in Task 1, and CD1D, PLA2G16, DACH1, and SOWAHA in Task 2. According to The Cancer Genome Atlas dataset, these genes are all prognostic factors for pancreatic cancer. Thus, the feasibility of using our deep learning-based method for the selection of genes associated with pancreatic cancer development and prognosis was confirmed.

Sex Differences in Cancer Genomes: Much Learned, More Unknown.

Cancer is a leading cause of death worldwide. Sex influences cancer in a bewildering variety of ways. In some cancer types, it affects prevalence; in others, genomic profiles, response to treatment, or mortality. In some, sex seems to have little or no influence. How and when sex influences cancer initiation and progression remain a critical gap in our understanding of cancer, with direct relevance to precision medicine. Here, we note several factors that complicate our understanding of sex differences: representativeness of large cohorts, confounding with features such as ancestry, age, obesity, and variability in clinical presentation. We summarize the key resources available to study molecular sex differences and suggest some likely directions for improving our understanding of how patient sex influences cancer behavior.

Systematic identification of novel cancer genes through analysis of deep shRNA perturbation screens.

Systematic perturbation screens provide comprehensive resources for the elucidation of cancer driver genes. The perturbation of many genes in relatively few cell lines in such functional screens necessitates the development of specialized computational tools with sufficient statistical power. Here we developed APSiC (Analysis of Perturbation Screens for identifying novel Cancer genes) to identify genetic drivers and effectors in perturbation screens even with few samples. Applying APSiC to the shRNA screen Project DRIVE, APSiC identified well-known and novel putative mutational and amplified cancer genes across all cancer types and in specific cancer types. Additionally, APSiC discovered tumor-promoting and tumor-suppressive effectors, respectively, for individual cancer types, including genes involved in cell cycle control, Wnt/ß-catenin and hippo signalling pathways. We functionally demonstrated that LRRC4B, a putative novel tumor-suppressive effector, suppresses proliferation by delaying cell cycle and modulates apoptosis in breast cancer. We demonstrate APSiC is a robust statistical framework for discovery of novel cancer genes through analysis of large-scale perturbation screens. The analysis of DRIVE using APSiC is provided as a web portal and represents a valuable resource for the discovery of novel cancer genes.

Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer.

The molecular mechanism of bone metastasis in breast cancer is largely unknown. Herein, we aimed to identify the key genes and long non-coding RNAs (lncRNAs) related to the bone metastasis of breast cancer using a bioinformatics approach. We screened differentially expressed genes and lncRNAs between normal breast and breast cancer bone metastasis samples using the GSE66206 dataset from the Gene Expression Omnibus. We also constructed a differentially expressed lncRNA-mRNA interaction network and analyzed the node degrees to identify the driving genes. After finding potential pathogenic modules of breast cancer bone metastasis, we identified breast cancer bone metastasis-related modules and functional enrichment analysis of the genes and lncRNAs in the modules. Based on the above analysis, we constructed a differentially expressed lncRNA-mRNA network related to bone metastasis in breast cancer and identified core driver genes, including BNIP3 and the lncRNA RP11-317-J19.1. The role of core driver genes and lncRNAs in the network implies their biological functions in regulating bone development and remodeling. Thus, targeting the core driver genes and lncRNAs in the network may be a promising therapeutic strategy to manage bone metastasis.