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Since 2017, we have used IonTorrent NGS platform in our hospital to diagnose and treat cancer. Analyzing variants at each run requires considerable time, and we are still struggling with some variants that appear correct on the metrics at first, but are found to be negative upon further investigation. Can any machine learning algorithm (ML) help us classify NGS variants? This has led us to investigate which ML can fit our NGS data and to develop a tool that can be routinely implemented to help biologists. Currently, one of the greatest challenges in medicine is processing a significant quantity of data. This is particularly true in molecular biology with the advantage of next-generation sequencing (NGS) for profiling and identifying molecular tumors and their treatment. In addition to bioinformatics pipelines, artificial intelligence (AI) can be valuable in helping to analyze mutation variants. Generating sequencing data from patient DNA samples has become easy to perform in clinical trials. However, analyzing the massive quantities of genomic or transcriptomic data and extracting the key biomarkers associated with a clinical response to a specific therapy requires a formidable combination of scientific expertise, biomolecular skills and a panel of bioinformatic and biostatistic tools, in which artificial intelligence is now successful in developing future routine diagnostics. However, cancer genome complexity and technical artifacts make identifying real variants challenging. We present a machine learning method for classifying pathogenic single nucleotide variants (SNVs), single nucleotide polymorphisms (SNPs), multiple nucleotide variants (MNVs), insertions, and deletions detected by NGS from different types of tumor specimens, such as: colorectal, melanoma, lung and glioma cancer. We compared our NGS data to different machine learning algorithms using the k-fold cross-validation method and to neural networks (deep learning) to measure the performance of the different ML algorithms and determine which one is a valid model for confirming NGS variant calls in cancer diagnosis. We trained our machine learning with 70% of our data samples, extracted from our local database (our data structure had 7 parameters: chromosome, position, exon, variant allele frequency, minor allele frequency, coverage and protein description) and validated it with the 30% remaining data. The model offering the best accuracy was chosen and implemented in the NGS analysis routine. Artificial intelligence was developed with the R script language version 3.6.0. We trained our model on 70% of 102,011 variants. Our best error rate (0.22%) was found with random forest machine learning (ntree = 500 and mtry = 4), with an AUC of 0.99. Neural networks achieved some good scores. The final trained model with the neural network achieved an accuracy of 98% and an ROC-AUC of 0.99 with validation data. We tested our RF model to interpret more than 2000 variants from our NGS database: 20 variants were misclassified (error rate < 1%). The errors were nomenclature problems and false positives. After adding false positives to our training database and implementing our RF model routinely, our error rate was always < 0.5%. The RF model shows excellent results for oncosomatic NGS interpretation and can easily be implemented in other molecular biology laboratories. AI is becoming increasingly important in molecular biomedical analysis and can be very helpful in processing medical data. Neural networks show a good capacity in variant classification, and in the future, they may be useful in predicting more complex variants.

The human nuclear receptor (NR) superfamily comprises 48 ligand-dependent transcription factors that play regulatory roles in physiology and pathophysiology. In cancer, NRs have long served as predictors of disease stratification, treatment response, and clinical outcome. The Cancer Genome Atlas (TCGA) Pan-Cancer project provides a wealth of genetic data for a large number of human cancer types. Here, we examined NR transcriptional activity in 8,526 patient samples from 33 TCGA ‘Pan-Cancer’ diseases and 11 ‘Pan-Cancer’ organ systems using RNA sequencing data. The web-based Kaplan-Meier (KM) plotter tool was then used to evaluate the prognostic potential of NR gene expression in 21/33 cancer types. Although, most NRs were significantly underexpressed in cancer, NR expression (moderate to high expression levels) was predominantly restricted (46%) to specific tissues, particularly cancers representing gynecologic, urologic, and gastrointestinal ‘Pan-Cancer’ organ systems. Intriguingly, a relationship emerged between recurrent positive pairwise correlation of Class IV NRs in most cancers. NR expression was also revealed to play a profound effect on patient overall survival rates, with ≥5 prognostic NRs identified per cancer type. Taken together, these findings highlighted the complexity of NR transcriptional networks in cancer and identified novel therapeutic targets for specific cancer types.

Tumorigenesis begins long before the growth of a clinically detectable lesion and, indeed, even before any of the usual morphological correlates of pre-malignancy are recognizable. Field cancerization, which is the replacement of the normal cell population by a cancer-primed cell population that may show no morphological change, is now recognized to underlie the development of many types of cancer, including the common carcinomas of the lung, colon, skin, prostate and bladder. Field cancerization is the consequence of the evolution of somatic cells in the body that results in cells that carry some but not all phenotypes required for malignancy. Here, we review the evidence of field cancerization across organs and examine the biological mechanisms that drive the evolutionary process that results in field creation. We discuss the clinical implications, principally, how measurements of the cancerized field could improve cancer risk prediction in patients with pre-malignant disease.

Key Points The oncoprotein BRAF is frequently activated due to genetic alterations in tumours promoting deregulation of RAF–MEK–ERK signalling. Targeting BRAF with inhibitors is a validated therapeutic strategy for a substantial proportion of cancer patients. RAF inhibitors alone or in combination with MEK inhibitors have elicited dramatic responses and prolonged the survival of patients with melanoma whose tumours harbour mutationally activated BRAF-V600. However, their effectiveness is limited by the development of drug resistance, frequently by mechanisms that promote reactivation of RAF–ERK signalling in the presence of the drug. In BRAF-V600 tumours other than melanoma, or in tumours carrying BRAF alterations other than the BRAF-V600 mutation, current clinical RAF inhibitors have shown modest effectiveness. RAF inhibitors have unique biochemical properties that account for their wide therapeutic window, on-target toxicities and major mechanisms of resistance. RAF dimerization is a common mechanism of both intrinsic and acquired resistance to current clinical RAF inhibitors vemurafenib and dabrafenib, which stabilize the αC-helix of RAF kinase in the OUT position. These compounds effectively inhibit monomeric mutant BRAF but fail to inhibit dimeric RAF. Structurally, inhibitor resistance due to RAF dimerization is the result of negative allostery for inhibitor binding to the second protomer of the RAF dimer, once the first is bound to an inhibitor. Next-generation RAF inhibitors that stabilize the αC-helix of RAF kinase in the active (IN) position will inhibit RAF monomers and dimers, but they are predicted to have a narrow therapeutic window due to inhibition of wild-type BRAF in normal cells. Thus, combinatorial approaches with current clinical inhibitors may be beneficial. Paradoxical pathway activation (allosteric priming) is a critical adverse event observed with most RAF inhibitors in the presence of RAS. Its effect on downstream signalling is currently ameliorated with the combined use of MEK inhibitors. Several structurally diverse, next-generation RAF inhibitors are under preclinical or clinical development and may be effective in BRAF-mutant tumours that are resistant to current clinical RAF inhibitors. Several types of human tumour are dependent on mutations in BRAF. This led to the development of RAF inhibitors, which prolong patient survival but are limited by resistance. This Review discusses the recent advances in our understanding of BRAF oncogenic signalling, RAF inhibitor activity and the implementation of this knowledge for the development of next-generation inhibitors. The discovery that a subset of human tumours is dependent on mutationally deregulated BRAF kinase intensified the development of RAF inhibitors to be used as potential therapeutics. The US Food and Drug Administration (FDA)-approved second-generation RAF inhibitors vemurafenib and dabrafenib have elicited remarkable responses and improved survival of patients with BRAF-V600E/K melanoma, but their effectiveness is limited by resistance. Beyond melanoma, current clinical RAF inhibitors show modest efficacy when used for colorectal and thyroid BRAF-V600E tumours or for tumours harbouring BRAF alterations other than the V600 mutation. Accumulated experimental and clinical evidence indicates that the complex biochemical mechanisms of RAF kinase signalling account both for the effectiveness of RAF inhibitors and for the various mechanisms of tumour resistance to them. Recently, a number of next-generation RAF inhibitors, with diverse structural and biochemical properties, have entered preclinical and clinical development. In this Review, we discuss the current understanding of RAF kinase regulation, mechanisms of inhibitor action and related clinical resistance to these drugs. The recent elucidation of critical structural and biochemical aspects of RAF inhibitor action, combined with the availability of a number of structurally diverse RAF inhibitors currently in preclinical and clinical development, will enable the design of more effective RAF inhibitors and RAF-inhibitor-based therapeutic strategies, tailored to different clinical contexts.

Key Points Metastases, and complications of their treatment, are significant causes of patient morbidity and mortality. Drugging metastasis pathways represents a potential new therapeutic opportunity. Most preclinical experiments demonstrate partial prevention of metastasis rather than shrinkage of existing lesions. These data would apply to the prevention of an initial metastasis in a high-risk patient, or the prevention of additional metastases in patients with treated, limited metastatic disease. Metastatic colonization represents the best 'open' therapeutic window in metastasis. It is the progressive outgrowth of tumour cells in a distant location, influenced by tumour cell signalling and interaction with a modified microenvironment (the formation of a premetastatic niche, alterations in the extracellular matrix and stromal cells, innate and T cell immunity and altered vascular supply). Denosumab, a monoclonal antibody that blocks the receptor activator of NF-κB ligand (RANKL; which is involved in the bone metastatic process), provides evidence that metastasis can be successfully drugged. Denosumab clinical trials used an interesting primary end point — skeletal-related events (SREs). The development of metastasis prevention agents may be hindered by their cytostatic nature, which will not result in shrinkage of established metastatic lesions (responses) in early clinical testing. New clinical trial designs for primary and secondary metastasis prevention are needed to lower the time, cost and cohort sizes of traditional adjuvant trials. It is likely that a single metastasis-preventive agent will not be maximally effective. As for HIV, a combination of distinct classes of drugs, given early and continuously, will be key. Tumour metastasis is a major contributor to the mortality of cancer patients, so why is this phase of cancer pathogenesis not routinely targeted? This Review discusses the possible strategies — including preclinical research, combination therapies and clinical trial designs — that could be developed to target metastasis. Tumour metastasis, the movement of tumour cells from a primary site to progressively colonize distant organs, is a major contributor to the deaths of cancer patients. Therapeutic goals are the prevention of an initial metastasis in high-risk patients, shrinkage of established lesions and prevention of additional metastases in patients with limited disease. Instead of being autonomous, tumour cells engage in bidirectional interactions with metastatic microenvironments to alter antitumour immunity, the extracellular milieu, genomic stability, survival signalling, chemotherapeutic resistance and proliferative cycles. Can targeting of these interactions significantly improve patient outcomes? In this Review preclinical research, combination therapies and clinical trial designs are re-examined.

The development of therapeutic approaches that target BRCA-mutant tumours has led to the possibility of expanding the range of patients who may benefit from such strategies. Tumours with 'BRCAness', a similar phenotype to germline BRCA-mutant tumours, are increasingly being identified, and this Opinion article discusses the advances and challenges in this context. Over the past 20 years, there has been considerable progress in our understanding of the biological functions of the BRCA1 and BRCA2 cancer susceptibility genes. This has led to the development of new therapeutic approaches that target tumours with loss-of-function mutations in either BRCA1 or BRCA2 . Tumours that share molecular features of BRCA-mutant tumours — that is, those with 'BRCAness' — may also respond to similar therapeutic approaches. Several paradigm shifts require a reassessment of the concept of BRCAness, how this property is assayed and its relevance to our understanding of tumour biology and the treatment of cancer.

Key Points Metaplasia is the replacement of one differentiated cell type with another mature differentiated cell type that is not normally present in that tissue. Metaplasia, when persistent, can be a precursor to dysplasia, which can in turn progress to carcinoma. As a result, recognition of metaplasia through screening and surveillance modalities is important and could reveal potential strategies for both cancer prevention and therapy. Metaplasia is an adaptive response to injurious agents, which are largely environmental in nature (for example, acid, bile, cigarette smoke and alcohol), but is also influenced by the actions of microorganisms (for example, Helicobacter pylori and human papillomavirus (HPV)). Different types of metaplasia exist, depending upon the tissue source: squamous, intestinal and acinar–ductal. The cell of origin has been postulated to be from the gastric cardia in oesophageal intestinal metaplasia and to be triggered by loss of parietal cells in gastric intestinal metaplasia. Metaplastic cell-autonomous (for example, mutant KRAS signalling) and non-cell-autonomous mechanisms contribute to the development and maintenance of metaplasia. Metaplasia, the replacement of one differentiated somatic cell type with another in the same tissue, is a precursor to dysplasia and eventually carcinoma. There are shared principles across different types of tissue metaplasia that may be helpful in clinical considerations. Metaplasia is the replacement of one differentiated somatic cell type with another differentiated somatic cell type in the same tissue. Typically, metaplasia is triggered by environmental stimuli, which may act in concert with the deleterious effects of microorganisms and inflammation. The cell of origin for intestinal metaplasia in the oesophagus and stomach and for pancreatic acinar–ductal metaplasia has been posited through genetic mouse models and lineage tracing but has not been identified in other types of metaplasia, such as squamous metaplasia. A hallmark of metaplasia is a change in cellular identity, and this process can be regulated by transcription factors that initiate and/or maintain cellular identity, perhaps in concert with epigenetic reprogramming. Universally, metaplasia is a precursor to low-grade dysplasia, which can culminate in high-grade dysplasia and carcinoma. Improved clinical screening for and surveillance of metaplasia might lead to better prevention or early detection of dysplasia and cancer.

Lynch syndrome is caused by heterozygous mutations and epimutations in mismatch repair genes, which lead to specific pathologies, including increased risk of multiple types of cancer and microsatellite instability. Lynch syndrome has been pivotal to the history of understanding hereditary cancer-prone syndromes and continues to lead the way in our understanding of the risk and treatment of familial cancers. Lynch syndrome, which is now recognized as the most common hereditary colorectal cancer condition, is characterized by the predisposition to a spectrum of cancers, primarily colorectal cancer and endometrial cancer. We chronicle over a century of discoveries that revolutionized the diagnosis and clinical management of Lynch syndrome, beginning in 1895 with Warthin's observations of familial cancer clusters, through the clinical era led by Lynch and the genetic era heralded by the discovery of causative mutations in mismatch repair (MMR) genes, to ongoing challenges.

Renal Cell Carcinoma (RCC) is the most common form of kidney cancer, with clear cell RCC (ccRCC) representing about 85% of all RCC tumors. There are limited curable treatments available for metastatic ccRCC because this disease is unresponsive to conventional targeted systemic pharmacotherapy. Exosomes (Exo) are small extracellular vesicles (EVs) secreted from cancer cells with marked roles in tumoral signaling and pharmacological resistance. Ketoconazole (KTZ) is an FDA approved anti-fungal medication which has been shown to suppress exosome biogenesis and secretion, yet its role in ccRCC has not been identified. A time-course, dose-dependent analysis revealed that KTZ selectively decreased secreted Exo in tumoral cell lines. Augmented Exo secretion was further evident by decreased expression of Exo biogenesis (Alix and nSMase) and secretion (Rab27a) markers. Interestingly, KTZ-mediated inhibition of Exo biogenesis was coupled with inhibition of ERK1/2 activation. Next, selective inhibitors were employed and showed ERK signaling had a direct role in mediating KTZ’s inhibition of exosomes. In sunitinib resistant 786-O cells lines, the addition of KTZ potentiates the efficacy of sunitinib by causing Exo inhibition, decreased tumor proliferation, and diminished clonogenic ability of RCC cells. Our findings suggest that KTZ should be explored as an adjunct to current RCC therapies.

Key Points Several tumours either develop in the skeleton, such as multiple myeloma, or metastasize to bone, such as breast and prostate cancers. The skeleton provides a unique microenvironment that supports the development of these tumours, although the nature of this microenvironment has until recently been poorly defined. Our understanding of the early, crucial events of tumour cell colonization, survival and dormancy, and reactivation of dormant cancer cells has been limited. However, progress in single cell imaging and molecular techniques has provided new insights. Tumour cell dormancy in the skeleton is induced by interactions with specific cells in the local bone microenvironment. Cells of the osteoblast lineage, present on the endosteal bone surface, provide a supportive niche to keep tumour cells in a dormant state. Reactivation of dormant tumour cells is mediated by extrinsic changes in the bone microenvironment. Osteoclasts, by remodelling the endosteal bone surface, represent one mechanism by which dormant cells can be reactivated. Our improved understanding of the control of tumour dormancy in the skeleton has revealed new therapeutic opportunities. These include using bone-active drugs to promote long-term tumour cell dormancy, or conversely, promoting reactivation and targeting dormant cells to eradicate them and 'cure' tumours that develop in bone. This Review summarizes progress in our understanding of the mechanisms by which different bone cell types support tumour cell dormancy and reactivation, and highlights new therapeutic approaches to control dormancy and bone metastasis by targeting the bone microenvironment. During the past decade preclinical studies have defined many of the mechanisms used by tumours to hijack the skeleton and promote bone metastasis. This has led to the development and widespread clinical use of bone-targeted drugs to prevent skeletal-related events. This understanding has also identified a critical dependency between colonizing tumour cells and the cells of bone. This is particularly important when tumour cells first arrive in bone, adapt to their new microenvironment and enter a long-lived dormant state. In this Review, we discuss the role of different bone cell types in supporting disseminated tumour cell dormancy and reactivation, and highlight the new opportunities this provides for targeting the bone microenvironment to control dormancy and bone metastasis.