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Osteosarcoma (OS) is the most common primary malignant bone tumor in children and adolescents. It is characterized by highly complex karyotypes with structural and numerical chromosomal alterations. The observed OS-specific characteristics in localization and frequencies of chromosomal breakages strongly implicate a specific set of responsible driver genes or a specific mechanism of fragility induction. In this study, a comprehensive assessment of somatic copy number alterations (SCNAs) was performed in 160 OS samples using whole-genome CytoScan High Density arrays (Affymetrix, Santa Clara, CA). Genes or regions frequently targeted by SCNAs were identified. Breakage analysis revealed OS specific unstable regions in which well-known OS tumor suppressor genes, including TP53, RB1, WWOX, DLG2 and LSAMP are located. Certain genomic features, such as transposable elements and non-B DNA-forming motifs were found to be significantly enriched in the vicinity of chromosomal breakage sites. A complex breakage pattern-chromothripsis-has been suggested as a widespread phenomenon in OS. It was further demonstrated that hyperploidy and in particular chromothripsis were strongly correlated with OS patient clinical outcome. The revealed OS-specific fragility pattern provides novel clues for understanding the biology of OS. [ABSTRACT FROM AUTHOR]

Introduction: Defects in tissue repair or wound healing pose a clinical, economic and social problem worldwide. Despite decades of studies, there have been few effective therapeutic treatments. Areas covered: We discuss the possible reasons for why growth factor therapy did not succeed. We point out the lack of human disorder-relevant animal models as another blockade for therapeutic development. We summarize the recent discovery of secreted heat shock protein-90 (Hsp90) as a novel wound healing agent. Expert commentary: Wound healing is a highly complex and multistep process that requires participations of many cell types, extracellular matrices and soluble molecules to work together in a spatial and temporal fashion within the wound microenvironment. The time that wounds remain open directly correlates with the clinical mortality associated with wounds. This time urgency makes the healing process impossible to regenerate back to the unwounded stage, rather forces it to take many shortcuts in order to protect life. Therefore, for therapeutic purpose, it is crucial to identify so-called ‘driver genes’ for the life-saving phase of wound closure. Keratinocyte-secreted Hsp90α was discovered in 2007 and has shown the promise by overcoming several key hurdles that have blocked the effectiveness of growth factors during wound healing. [ABSTRACT FROM PUBLISHER]

The cancer atavistic theory suggests that carcinogenesis is a reverse evolution process. It is thus of great interest to explore the evolutionary origins of cancer driver genes and the relevant mechanisms underlying the carcinogenesis. Moreover, the evolutionary features of cancer driver genes could be helpful in selecting cancer biomarkers from high-throughput data. In this study, through analyzing the cancer endogenous molecular networks, we revealed that the subnetwork originating from eukaryota could control the unlimited proliferation of cancer cells, and the subnetwork originating from eumetazoa could recapitulate the other hallmarks of cancer. In addition, investigations based on multiple datasets revealed that cancer driver genes were enriched in genes originating from eukaryota, opisthokonta, and eumetazoa. These results have important implications for enhancing the robustness of cancer prognosis models through selecting the gene signatures by the gene age information. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma is one of the most mortal and prevalent cancers with increasing incidence worldwide. Elucidating genetic driver genes for prognosis and palindromia of hepatocellular carcinoma helps managing clinical decisions for patients. In this study, the high-throughput RNA sequencing data on platform IlluminaHiSeq of hepatocellular carcinoma were downloaded from The Cancer Genome Atlas with 330 primary hepatocellular carcinoma patient samples. Stable key genes with differential expressions were identified with which Kaplan--Meier survival analysis was performed using Cox proportional hazards test in R language. Driver genes influencing the prognosis of this disease were determined using clustering analysis. Functional analysis of driver genes was performed by literature search and Gene Set Enrichment Analysis. Finally, the selected driver genes were verified using external dataset GSE40873. A total of 5781 stable key genes were identified, including 156 genes definitely related to prognoses of hepatocellular carcinoma. Based on the significant key genes, samples were grouped into five clusters which were further integrated into high- and low-risk classes based on clinical features. TMEM88, CCL14, and CLEC3B were selected as driver genes which clustered high-/ low-risk patients successfully (generally, p = 0.0005124445). Finally, survival analysis of the high-/low-risk samples from external database illustrated significant difference with p value 0.0198. In conclusion, TMEM88, CCL14, and CLEC3B genes were stable and available in predicting the survival and palindromia time of hepatocellular carcinoma. These genes could function as potential prognostic genes contributing to improve patients' outcomes and survival. [ABSTRACT FROM AUTHOR]

Purpose: Germline mutations in tumour suppressor genes cause various cancers. These genes are also somatically mutated in sporadic tumours. We hypothesized that there may also be cancer-related germline variants in the genes commonly mutated in sporadic breast tumours.Methods: After excluding the well-characterized breast cancer (BC) genes, we screened 15 novel genes consistently classified as BC driver genes in next-generation sequencing approaches for single nucleotide polymorphisms (SNPs). Altogether 40 SNPs located in the core promoter, 5'- and 3'-UTR or which were nonsynonymous SNPs were genotyped in 782 Swedish incident BC cases and 1,559 matched controls. After statistical analyses, further evaluations related to functional prediction and signatures of selection were performed.Results: TBX3 was associated with BC risk (rs2242442: OR = 0.76, 95% CI 0.64-0.92, dominant model) and with less aggressive tumour characteristics. An association with BC survival and aggressive tumour characteristics was detected for the genes ATR (rs2227928: HR = 1.63; 95% CI 1.00-2.64, dominant model), RUNX1 (rs17227210: HR = 3.50, 95% CI 1.42-8.61, recessive model) and TTN (rs2303838: HR = 2.36; 95% CI 1.04-5.39; rs2042996: HR = 2.28; 95% CI 1.19-4.37, recessive model). According to the experimental ENCODE data all these SNPs themselves or SNPs in high linkage disequilibrium with them (r 2 ≥ 0.80) were located in regulatory regions. RUNX1 and TTN showed also several signatures of positive selection.Conclusion: The study gave evidence that germline variants in BC driver genes may have impact on BC risk and/or survival. Future studies could discover further germline variants in known or so far unknown driver genes which contribute to cancer development. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC), the main type of liver cancer, is the second most lethal tumor worldwide, with a 5-year survival rate of only 18%. Driver genes facilitate cancer cell growth and spread in the tumor microenvironment. Here, a comprehensive driver gene signature for the prognosis of HCC was developed., Methods: HCC driver genes were analyzed comprehensively to develop a better prognostic signature. The dataset of HCC patients included mRNA sequencing data and clinical information from the TCGA, the ICGC, and the Guangxi Medical University Cancer Hospital cohorts. First, LASSO was performed to develop a prognostic signature for differentially expressed driver genes in the TCGA cohort. Then, the robustness of the signature was assessed using survival and time-dependent ROC curves. Furthermore, independent predictors were determined using univariate and multivariate Cox regression analyses. Stepwise multi-Cox regression analysis was employed to identify significant variables for the construction of a nomogram that predicts survival rates. Functional analysis by Spearman correlation analysis, enrichment analysis (GO, KEGG, and GSEA), and immunoassay (ssGSEA and xCell) were performed., Result: A 4-driver gene signature (CLTC, DNMT3A, GMPS, and NRAS) was successfully constructed and showed excellent predictive efficiency in three cohorts. The nomogram indicated high predictive accuracy for the 1-, 3-, and 5-year prognoses of HCC patients, which included clinical information and risk score. Enrichment analysis revealed that driver genes were involved in regulating oncogenic processes, including the cell cycle and metabolic pathways, which were associated with the progression of HCC. ssGSEA and xCell showed differences in immune infiltration and the immune microenvironment between the two risk groups., Conclusion: The 4-driver gene signature is closely associated with the survival prediction of HCC and is expected to provide new insights into targeted therapy for HCC patients., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Background: Cancer is a complex disease which is characterized by the accumulation of genetic alterations during the patient's lifetime. With the development of the next-generation sequencing technology, multiple omics data, such as cancer genomic, epigenomic and transcriptomic data etc., can be measured from each individual. Correspondingly, one of the key challenges is to pinpoint functional driver mutations or pathways, which contributes to tumorigenesis, from millions of functional neutral passenger mutations. Results: In this paper, in order to identify driver genes effectively, we applied a generalized additive model to mutation profiles to filter genes with long length and constructed a new gene-gene interaction network. Then we integrated the mutation data and expression data into the gene-gene interaction network. Lastly, greedy algorithm was used to prioritize candidate driver genes from the integrated data. We named the proposed method Length-Net-Driver (LNDriver). Conclusions: Experiments on three TCGA datasets, i.e., head and neck squamous cell carcinoma, kidney renal clear cell carcinoma and thyroid carcinoma, demonstrated that the proposed method was effective. Also, it can identify not only frequently mutated drivers, but also rare candidate driver genes. [ABSTRACT FROM AUTHOR]

Sequencing has identified millions of somatic mutations in human cancers, but distinguishing cancer driver genes remains a major challenge. Numerous methods have been developed to identify driver genes, but evaluation of the performance of these methods is hindered by the lack of a gold standard, that is, bona fide driver gene mutations. Here, we establish an evaluation framework that can be applied to driver gene prediction methods. We used this framework to compare the performance of eight such methods. One of these methods, described here, incorporated a machinelearning– based ratiometric approach. We show that the driver genes predicted by each of the eight methods vary widely. Moreover, the P values reported by several of the methods were inconsistent with the uniform values expected, thus calling into question the assumptions that were used to generate them. Finally, we evaluated the potential effects of unexplained variability in mutation rates on false-positive driver gene predictions. Our analysis points to the strengths and weaknesses of each of the currently available methods and offers guidance for improving them in the future. [ABSTRACT FROM AUTHOR]

The introduction of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) in the therapy of non-small cell lung cancer (NSCLC) with activating mutations of the EGF receptor has opened a new area of lung cancer treatment strategies and led to an enthusiastic search for additional genetic aberrations. Genetic drivers such as EML4-ALK (EML4: echinoderm microtubule-associated protein-like 4; ALK: anaplastic lymphoma kinase) and proto-oncogene tyrosine protein kinase transcribed from the ROS1-gene (ROS1) rearrangements have been detected and specific treatment options have been developed. A new approach to treatment in lung cancer is immunotherapy by antibodies interfering with immune checkpoint controls. Diagnostic and predictive immunohistochemical staining and molecular tests have to follow specific rules, if applied in daily practice. The Austrian Working Group on Pulmonary Pathology and Oncology (AWGPPO) has presented an updated version of the previous recommendations published in 2013. Questions raised during the past 3 years will be addressed: selection of tissue, order of diagnostic immunohistochemical and molecular tests, 'reflex' testing, the issue of resistance mechanisms, significance of liquid biopsies, and use and interpretation of antibody reactions for immune checkpoint markers. [ABSTRACT FROM AUTHOR]

Despite substantial progress in understanding the mechanisms of carcinogenesis and fighting oncology diseases, cancer mortality remains rather high. Therefore, there is a striving to reduce this mortality to the level determined by endogenous biological factors. The review analyzes the mutations that lead to cell malignant transformation and describes the contribution that self-renewal of adult tissues makes to tumorigenesis. Cancer progression is considered as a development of a complicated system where cells mutate, evolve, and are subject to selection. Cancer paradoxes are described in conclusion. [ABSTRACT FROM AUTHOR]

The statistics are alarming; pancreatic ductal adenocarcinoma (PDA) will be the second leading cause of death amongst all cancers by 2020. More worrisome is that incidence is on the rise, and without more effective cancer control of this disease, the trajectory of the virtually indistinguishable rates of incidence and mortality will remain the reality for years to come. Advances in genomics are beginning to clarify the key issues about the pathogenesis of this aggressive tumour type. New insights into classic pathogenic driver genes, such as KRAS , CDKN2A , TP53 and SMAD4 , are portraying alternative roles for these genes beyond their function at the preneoplastic level including metastatic dissemination and chemoresistance. Clinically relevant molecular subtypes have recently emerged, which will aid oncologists in making more informed treatment decisions to improve outcomes in the future. A wealth of data surrounding these issues has been generated over the last 5 years. Below, we attempt to bring readers up to speed on recent research findings in PDA. [ABSTRACT FROM AUTHOR]

The central challenges in tumor sequencing studies is to identify driver genes and pathways, investigate their functional relationships, and nominate drug targets. The efficiency of these analyses, particularly for infrequently mutated genes, is compromised when subjects carry different combinations of driver mutations. Mutual exclusivity analysis helps address these challenges. To identify mutually exclusive gene sets (MEGS), we developed a powerful and flexible analytic framework based on a likelihood ratio test and a model selection procedure. Extensive simulations demonstrated that our method outperformed existing methods for both statistical power and the capability of identifying the exact MEGS, particularly for highly imbalanced MEGS. Our method can be used for de novo discovery, for pathway-guided searches, or for expanding established small MEGS. We applied our method to the whole-exome sequencing data for 13 cancer types from The Cancer Genome Atlas (TCGA). We identified multiple previously unreported non-pairwise MEGS in multiple cancer types. For acute myeloid leukemia, we identified a MEGS with five genes ( FLT3 , IDH2 , NRAS , KIT , and TP53 ) and a MEGS ( NPM1 , TP53 , and RUNX1 ) whose mutation status was strongly associated with survival (p = 6.7 × 10 −4 ). For breast cancer, we identified a significant MEGS consisting of TP53 and four infrequently mutated genes ( ARID1A , AKT1 , MED23 , and TBL1XR1 ), providing support for their role as cancer drivers. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) is the most prevalent cancer in women and a major public health problem in Morocco. Several Moroccan studies have focused on studying this disease, but more are needed, especially at the genetic and molecular levels. Therefore, we investigated the potential association of several functional germline variants in the genes commonly mutated in sporadic breast cancer.Methods: In this case-control study, we examined 36 single nucleotide polymorphisms (SNPs) in 13 genes (APOBEC3A, APOBEC3B, ARID1B, ATR, MAP3K1, MLL2, MLL3, NCOR1, RUNX1, SF3B1, SMAD4, TBX3, TTN), which were located in the core promoter, 5'-and 3'UTR or which were nonsynonymous SNPs to assess their potential association with inherited predisposition to breast cancer development. Additionally, we identified a ~29.5-kb deletion polymorphism between APOBEC3A and APOBEC3B and explored possible associations with BC. A total of 226 Moroccan breast cancer cases and 200 matched healthy controls were included in this study.Results: The analysis showed that12 SNPs in 8 driver genes, 4 SNPs in APOBEC3B gene and 1 SNP in APOBEC3A gene were associated with BC risk and/or clinical outcome at P ≤ 0.05 level. RUNX1_rs8130963 (odds ratio (OR) = 2.25; 95 % CI 1.42-3.56; P = 0.0005; dominant model), TBX3_rs8853 (OR = 2.04; 95 % CI 1.38-3.01; P = 0.0003; dominant model), TBX3_rs1061651 (OR= 2.14; 95 % CI1.43-3.18; P = 0.0002; dominant model), TTN_rs12465459 (OR = 2.02; 95 % confidence interval 1.33-3.07; P = 0.0009; dominant model), were the most significantly associated SNPs with BC risk. A strong association with clinical outcome were detected for the genes SMAD4 _rs3819122 with tumor size (OR = 0.45; 95 % CI 0.25-0.82; P = 0.009) and TTN_rs2244492 with estrogen receptor (OR = 0.45; 95 % CI 0.25-0.82; P = 0.009).Conclusion: Our results suggest that genetic variations in driver and APOBEC3 genes were associated with the risk of BC and may have impact on clinical outcome. However, the reported association between the deletion polymorphism and BC risk was not confirmed in the Moroccan population. These preliminary findings require replication in larger studies. [ABSTRACT FROM AUTHOR]

The emergence of targetted therapy has revolutionised the treatment of advanced NSCLC. Increasing numbers of driver genes and related targetted agents have supplied more powerful weapons for conquering NSCLC. Depending on whether there are clear targets and therapeutic effects, we can now rank targetted agents into three categories: agents with explicit targets and pure effects, agents with theoretical targets but with no effective biomarkers, agents with vague targets and lower effects. The latest clinical data on the safety and efficacy of monotherapy with three kinds of agents will be reviewed respectively in this article. [ABSTRACT FROM PUBLISHER]

Familial adenomatous polyposis ( FAP) and MUTYH-associated polyposis ( MAP) are inherited disorders associated with multiple colorectal adenomas that lead to a very high risk of colorectal cancer. The somatic mutations that drive adenoma development in these conditions have not been investigated comprehensively. In this study we performed analysis of paired colorectal adenoma and normal tissue DNA from individuals with FAP or MAP, sequencing 14 adenoma whole exomes (eight MAP, six FAP), 55 adenoma targeted exomes (33 MAP, 22 FAP) and germline DNA from each patient, and a further 63 adenomas by capillary sequencing (41 FAP, 22 MAP). With these data we examined the profile of mutated genes, the mutational signatures and the somatic mutation rates, observing significant diversity in the constellations of mutated driver genes in different adenomas, and loss-of-function mutations in WTX (9%; p < 9.99e-06), a gene implicated in regulation of the WNT pathway and p53 acetylation. These data extend our understanding of the early events in colorectal tumourigenesis in the polyposis syndromes. © 2015 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Over the last few years the increasing usage of "-omic" platforms, supported by next-generation sequencing, in the analysis of breast cancer samples has tremendously advanced our understanding of the disease. New driver and passenger mutations, rare chromosomal rearrangements and other genomic aberrations identified by whole genome and exome sequencing are providing missing pieces of the genomic architecture of breast cancer. High resolution maps of breast cancer methylomes and sequencing of the miRNA microworld are beginning to paint the epigenomic landscape of the disease. Transcriptomic profiling is giving us a glimpse into the gene regulatory networks that govern the fate of the breast cancer cell. At the same time, integrative analysis of sequencing data confirms an extensive intertumor and intratumor heterogeneity and plasticity in breast cancer arguing for a new approach to the problem. In this review, we report on the latest findings on the molecular characterization of breast cancer using NGS technologies, and we discuss their potential implications for the improvement of existing therapies. [ABSTRACT FROM AUTHOR]

Abnormal histone modifications (HMs) can promote the occurrence of breast cancer. To elucidate the relationship between HMs and gene expression, we analyzed HM binding patterns and calculated their signal changes between breast tumor cells and normal cells. On this basis, the influences of HM signal changes on the expression changes of breast cancer-related genes were estimated by three different methods. The results showed that H3K79me2 and H3K36me3 may contribute more to gene expression changes. Subsequently, 2109 genes with differential H3K79me2 or H3K36me3 levels during cancerogenesis were identified by the Shannon entropy and submitted to perform functional enrichment analyses. Enrichment analyses displayed that these genes were involved in pathways in cancer, human papillomavirus infection, and viral carcinogenesis. Univariate Cox, LASSO, and multivariate Cox regression analyses were then adopted, and nine potential breast cancer-related driver genes were extracted from the genes with differential H3K79me2/H3K36me3 levels in the TCGA cohort. To facilitate the application, the expression levels of nine driver genes were transformed into a risk score model, and its robustness was tested via time-dependent receiver operating characteristic curves in the TCGA dataset and an independent GEO dataset. At last, the distribution levels of H3K79me2 and H3K36me3 in the nine driver genes were reanalyzed in the two cell lines and the regions with significant signal changes were located., Competing Interests: Ling-Yu Wang, Lu-Qiang Zhang, Qian-Zhong Li and Hui Bai declare that they have no conflict of interest., (© The Author(s) 2023.)

Lung adenocarcinoma is one of the most common cancers in the world, and accurate diagnosis of lung nodules is an important factor in reducing its mortality. In the diagnosis of pulmonary nodules, artificial intelligence (AI) assisted diagnosis technology has been rapidly developed, so testing its effectiveness is conducive to promoting its important role in clinical practice. This paper introduces the background of early lung adenocarcinoma and lung nodule AI medical imaging, and then makes academic research on early lung adenocarcinoma and AI medical imaging, and finally summarizes the biological information. In the experimental part, the relationship analysis of 4 driver genes in group X and group Y showed that there were more abnormal invasive lung adenocarcinoma genes, and the maximum uptake value and uptake function of metabolic value were also higher. However, there was no significant correlation between mutations in the four driver genes and metabolic values, and the average accuracy of AI-based medical images was 3.88% higher than that of traditional images., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yin, Lu, Tong, Cheng and Zhang.)

Melanoma is a heterogenous malignancy with an unpredictable clinical course. Most patients who present in the clinic are diagnosed with primary melanoma, yet large-scale sequencing efforts have focused primarily on metastatic disease. In this study we sequence-profiled 524 American Joint Committee on Cancer Stage I-III primary tumours. Our analysis of these data reveals recurrent driver mutations, mutually exclusive genetic interactions, where two genes were never or rarely co-mutated, and an absence of co-occurring genetic events. Further, we intersected copy number calls from our primary melanoma data with whole-genome CRISPR screening data to identify the transcription factor interferon regulatory factor 4 (IRF4) as a melanoma-associated dependency. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland., (© 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.)

Colorectal carcinoma (CRC), the foremost basis of malignancy-related death worldwide, evolves due to the stepwise amassing of a succession of genetic and epigenetic modifications. Epigenetic indicators are significant molecular hallmarks of malignancy. They play a big role in disease pathogenesis and are involved in almost all important cancer-related pathways. They can also be used as clinically useful cancer biomarkers for diagnosis, prognosis, and predicting how well treatment will work. Similarly, as gene changes in the malignant growth genome, a subset of driver genes attempts to play a useful part in CRC. Advances in our understanding of abnormal methylation in CRC have led to the development of epigenetic changes as diagnostic and prognostic biomarkers, and role of non-coding RNAs as epigenetic controllers. Beforehand, mass transcriptomics analysis is used to group CRC based on its distinctive molecular and clinicopathological features for prediction and patient analysis. The development of single-cell transcriptomics flipped the script by making it possible to evaluate the expression levels of particular neoplastic cells within a single tumor. Cell motility, growth, development, proliferation, DNA replication, recombination, their relationships with transcriptomics, and the CRC transcriptome analysis, have shown improvements. Progress in the appraisal of epigenetic alterations in CRC and their clinical applications has indicated that these changes will be ordinarily utilized as molecular markers to coordinate the anticipation and treatment of CRC. Recent improvements in our understanding of CRC and progress in genomics have led to the discovery of a number of epigenetic changes that are strongly linked to both the start and spread of cancer., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

A large number of DNA copy number alterations (CNAs) exist in human breast cancers, and thus characterizing the most frequent CNAs is key to advancing therapeutics because it is likely that these regions contain breast tumor 'drivers' (i.e., cancer causal genes). This study aims to characterize the genomic landscape of breast cancer CNAs and identify potential subtype-specific drivers using a large set of human breast tumors and genetically engineered mouse (GEM) mammary tumors. Using a novel method called SWITCHplus, we identified subtype-specific DNA CNAs occurring at a 15 % or greater frequency, which excluded many well-known breast cancer-related drivers such as amplification of ERBB2, and deletions of TP53 and RB1. A comparison of CNAs between mouse and human breast tumors identified regions with shared subtype-specific CNAs. Additional criteria that included gene expression-to-copy number correlation, a DawnRank network analysis, and RNA interference functional studies highlighted candidate driver genes that fulfilled these multiple criteria. Numerous regions of shared CNAs were observed between human breast tumors and GEM mammary tumor models that shared similar gene expression features. Specifically, we identified chromosome 1q21-23 as a Basal-like subtype-enriched region with multiple potential driver genes including PI4KB, SHC1, and NCSTN. This step-wise computational approach based on a cross-species comparison is applicable to any tumor type for which sufficient human and model system DNA copy number data exist, and in this instance, highlights that a single region of amplification may in fact harbor multiple driver genes. [ABSTRACT FROM AUTHOR]

Background: Ovarian granulosa cell tumors (GCTs) are the most frequent sex cord-stromal tumors. Several studies have shown that a somatic mutation leading to a C134W substitution in the transcription factor FOXL2 appears in more than 95% of adult-type GCTs. Its pervasive presence suggests that FOXL2 is the main cancer driver gene. However, other mutations and genomic changes might also contribute to tumor formation and/or progression. Methods: We have performed a combined comparative genomic hybridization and transcriptomic analyses of 10 adult-type GCTs to obtain a picture of the genomic landscape of this cancer type and to identify new candidate co-driver genes. Results: Our results, along with a review of previous molecular studies, show the existence of highly recurrent chromosomal imbalances (especially, trisomy 14 and monosomy 22) and preferential co-occurrences (i.e. trisomy 14/monosomy 22 and trisomy 7/monosomy 16q). In-depth analyses showed the presence of recurrently broken, amplified/duplicated or deleted genes. Many of these genes, such as AKT1, RUNX1 and LIMA1, are known to be involved in cancer and related processes. Further genomic explorations suggest that they are functionally related. Conclusions: Our combined analysis identifies potential candidate genes, whose alterations might contribute to adult-type GCT formation/progression together with the recurrent FOXL2 somatic mutation. [ABSTRACT FROM AUTHOR]

Background: Cancer is widely regarded as a complex disease primarily driven by genetic mutations. A critical concern and significant obstacle lies in discerning driver genes amid an extensive array of passenger genes., Findings: We present a new method termed DriverMP for effectively prioritizing altered genes on a cancer-type level by considering mutated gene pairs. It is designed to first apply nonsilent somatic mutation data, protein‒protein interaction network data, and differential gene expression data to prioritize mutated gene pairs, and then individual mutated genes are prioritized based on prioritized mutated gene pairs. Application of this method in 10 cancer datasets from The Cancer Genome Atlas demonstrated its great improvements over all the compared state-of-the-art methods in identifying known driver genes. Then, a comprehensive analysis demonstrated the reliability of the novel driver genes that are strongly supported by clinical experiments, disease enrichment, or biological pathway analysis., Conclusions: The new method, DriverMP, which is able to identify driver genes by effectively integrating the advantages of multiple kinds of cancer data, is available at https://github.com/LiuYangyangSDU/DriverMP. In addition, we have developed a novel driver gene database for 10 cancer types and an online service that can be freely accessed without registration for users. The DriverMP method, the database of novel drivers, and the user-friendly online server are expected to contribute to new diagnostic and therapeutic opportunities for cancers., (© The Author(s) 2023. Published by Oxford University Press GigaScience.)

Epithelial ovarian cancer (EOC) is highly aggressive with poor patient outcomes, and a deeper understanding of ovarian cancer tumorigenesis could help guide future treatment development. We proposed an optimized hit network-target sets model to systematically characterize the underlying pathological mechanisms and intra-tumoral heterogeneity in human ovarian cancer. Using TCGA data, we constructed an epithelial ovarian cancer regulatory network in this study. We use three distinct methods to produce different HNSs for identification of the driver genes/nodes, core modules, and core genes/nodes. Following the creation of the optimized HNS (OHNS) by the integration of DN (driver nodes), CM (core module), and CN (core nodes), the effectiveness of various HNSs was assessed based on the significance of the network topology, control potential, and clinical value. Immunohistochemical (IHC), qRT-PCR, and Western blotting were adopted to measure the expression of hub genes and proteins involved in epithelial ovarian cancer (EOC). We discovered that the OHNS has two key advantages: the network's central location and controllability. It also plays a significant role in the illness network due to its wide range of capabilities. The OHNS and clinical samples revealed the endometrial cancer signaling, and the PI3K/AKT, NER, and BMP pathways. MUC16, FOXA1, FBXL2, ARID1A, COX15, COX17, SCO1, SCO2, NDUFA4L2, NDUFA, and PTEN hub genes were predicted and may serve as potential candidates for new treatments and biomarkers for EOC. This research can aid in better capturing the disease progression, the creation of potent multi-target medications, and the direction of the therapeutic community in the optimization of effective treatment regimens by various research objectives in cancer treatment.

The extent of focal chromosomal copy number aberrations (CNAs) in cancer has been uncovered through technical innovations, and this discovery has been critical for the identification of new cancer driver genes in genomics projects such as TCGA and ICGC. Unlike constitutive copy number variations (CNVs), focal CNAs are the result of many selection events during the evolution of cancer genomes. Therefore, it is possible that a single gene in a focal CNA gives the tumor a selective growth advantage. This concept has been instrumental in the discovery of new cancer driver genes. However, focal CNAs lack a consensus definition; therefore, we propose one based on pragmatic considerations. We also describe different strategies to identify focal CNAs and procedures to distinguish them from large CNAs and CNVs. [ABSTRACT FROM AUTHOR]

Highlights: [•] Chromosomal gains harbor key gene drivers of cervical carcinogenesis. [•] Key drivers enhance cell cycle, antiviral response, and inhibit cell differentiation. [•] Increased antiviral response contributes to decline of episomal human papillomavirus (HPV). [•] Decline of episomal HPV leads to release of integrated viral oncogenes (E6/E7). [Copyright &y& Elsevier]

The traditional way for discovering genes which drive cancer (namely cancer drivers) neglects the dynamic information of cancer development, even though it is well known that cancer progresses dynamically. To enhance cancer driver discovery, we expand cancer driver concept to dynamic cancer driver as a gene driving one or more bio-pathological transitions during cancer progression. Our method refers to the fact that cancer should not be considered as a single process but a compendium of altered biological processes causing the disease to develop over time. Reciprocally, different drivers of cancer can potentially be discovered by analysing different bio-pathological pathways. We propose a novel approach for causal inference of genes driving one or more core processes during cancer development (i.e. dynamic cancer driver). We use the concept of pseudotime for inferring the latent progression of samples along a biological transition during cancer and identifying a critical event when such a process is significantly deviated from normal to carcinogenic. We infer driver genes by assessing the causal effect they have on the process after such a critical event. We have applied our method to single-cell and bulk sequencing datasets of breast cancer. The evaluation results show that our method outperforms well-recognized cancer driver inference methods. These results suggest that including information of the underlying dynamics of cancer improves the inference process (in comparison with using static data), and allows us to discover different sets of driver genes from different processes in cancer. R scripts and datasets can be found at https://github.com/AndresMCB/DynamicCancerDriver., (© The Author(s) 2022. Published by Oxford University Press.)

Lung adenocarcinoma is a malignancy with a low overall survival and a poor prognosis. Studies have shown that lung adenocarcinoma progression relates to locus-specific/global changes in histone modifications. To explore the relationship between histone modification and gene expression changes, we focused on 11 histone modifications and quantitatively analyzed their influences on gene expression. We found that, among the studied histone modifications, H3K79me2 displayed the greatest impact on gene expression regulation. Based on the Shannon entropy, 867 genes with differential H3K79me2 levels during tumorigenesis were identified. Enrichment analyses showed that these genes were involved in 16 common cancer pathways and 11 tumors and were target-regulated by trans -regulatory elements, such as Tp53 and WT1. Then, an open-source computational framework was presented (https://github.com/zlq-imu/Identification-of-potential-LUND-driver-genes). Twelve potential driver genes were extracted from the genes with differential H3K79me2 levels during tumorigenesis. The expression levels of these potential driver genes were significantly increased/decreased in tumor cells, as assayed by RT-qPCR. A risk score model comprising these driver genes was further constructed, and this model was strongly negatively associated with the overall survival of patients in different datasets. The proportional hazards assumption and outlier test indicated that this model could robustly distinguish patients with different survival rates. Immune analyses and responses to immunotherapeutic and chemotherapeutic agents showed that patients in the high and low-risk groups may have distinct tendencies for clinical selection. Finally, the regions with clear H3K79me2 signal changes on these driver genes were accurately identified. Our research may offer potential molecular biomarkers for lung adenocarcinoma treatment., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

Development of primary mediastinal B-cell lymphoma (PMBL) is driven by cumulative genomic aberrations. We discovered a unique copy-neutral loss of heterozygosity (CN-LOH) landscape of PMBL which distinguishes this tumor from other B-cell malignancies, including the biologically related diffuse large B-cell lymphoma. Using single nucleotide polymorphism array analysis we identified large-scale CN-LOH lesions in 91% (30/33) of diagnostic PMBLs and both investigated PMBL-derived cell lines. Altogether, the cohort showed 157 extra-large (25.3-248.4 Mb) CN-LOH lesions affecting up to 14 chromosomes per case (mean of 4.4) and resulting in a reduction of heterozygosity an average of 9.9% (range 1.3-51%) of the genome. Predominant involvement of terminal chromosomal segments suggests the implication of B-cell specific crossover events in the pathogenesis of PMBL. Notably, CN-LOH stretches non-randomly clustered on 6p (60%), 15 (37.2%), and 17q (40%), and frequently co-occurred with homozygous mutations in the MHC I (6p21), B2M (15q15), and GNA13 (17q23) genes, respectively, as shown by preliminary whole-exome/genome sequencing data. Altogether, our findings implicate CN-LOH as a novel and distinct mutational process contributing to the molecular pathogenesis of PMBL. The aberration acting as "second hit" in the Knudson hypothesis, ranks as the major mechanism converting to homozygosity the PMBL-related driver genes. Screening of the cohort of 199 B cell leukemia/lymphoma whole-genomes revealed significant differences in the CN-LOH landscape of PMBL and other B-cell malignancies, including the biologically related diffuse large B-cell lymphoma., (© 2022 Wiley Periodicals LLC.)