Application of next-generation sequencing in clinical oncology to advance personalized treatment of cancer

Molecular methods in cancer diagnostics: a short review

BACKGROUND

One of the ailments with the greatest fatality rates in the 21st century is cancer. Globally, molecular methods are widely employed to treat cancer-related disorders, and the body of research on this subject is growing yearly. A thorough and critical summary of the data supporting molecular methods for illnesses linked to cancer is required.

OBJECTIVE

In order to guide clinical practice and future research, it is important to examine and summarize the systematic reviews (SRs) that evaluate the efficacy and safety of molecular methods for disorders associated to cancer.

METHODS

We developed a comprehensive search strategy to find relevant articles from electronic databases like PubMed, Google Scholar, Web of Science (WoS), or Scopus. We looked through the literature and determined which diagnostic methods in cancer genetics were particularly reliable. We used phrases like 'cancer genetics', genetic susceptibility, Hereditary cancer, cancer risk assessment, 'cancer diagnostic tools', cancer screening', biomarkers, and molecular diagnostics, reviews and meta-analyses evaluating the efficacy and safety of molecular therapies for cancer-related disorders. Research that only consider treatment modalities that don't necessitate genetic or molecular diagnostics fall under the exclusion criteria.

RESULTS

The results of this comprehensive review clearly demonstrate the transformative impact of molecular methods in the realm of cancer genetics.This review underscores how these technologies have empowered researchers and clinicians to identify and understand key genetic alterations that drive malignancy, ranging from point mutations to structural variations. Such insights are instrumental in pinpointing critical oncogenic drivers and potential therapeutic targets, thus opening the door for methods in precision medicine that can significantly improve patient outcomes.

LIMITATION

The search does not specify a timeframe for publication inclusion, it may have missed recent advancements or changes in the field's landscape of molecular methods for cancer. As a result, it may not have included the most recent developments in the field.

CONCLUSION

After conducting an in-depth study on the molecular methods in cancer genetics, it is evident that these cutting-edge technologies have revolutionized the field of oncology, providing researchers and clinicians with powerful tools to unravel the complexities of cancer at the genetic level. The integration of molecular methods techniques has not only enhanced our understanding of cancer etiology, progression, and treatment response but has also opened new avenues for personalized medicine and targeted therapies, leading to improved patient outcomes.

Epigenetic contribution to cancer

Epigenetics has transformed our understanding of cancer by revealing how changes in gene activity, which do not alter the DNA itself, can initiate and progress the disease. These changes include adjustments in DNA methylation, histone configuration, and non-coding RNA activity. For instance, DNA methylation can inactivate genes that typically protect against cancer, leading to broader genomic instability. Histone modifications can alter how tightly DNA is wound, influencing which genes are active or silenced; while non-coding RNAs can interfere with the messages that direct protein production, impacting cancer-related processes. Unlike genetic mutations, which are permanent and irreversible, epigenetic changes provide a malleable target for therapeutic intervention, allowing potentially reversible adjustments to gene expression patterns. This flexibility is essential in the complex landscape of cancer where static genetic solutions may be insufficient. Additionally, epigenetics bridges the gap between genetic predispositions and environmental influences on cancer, offering a comprehensive framework for understanding how lifestyle factors and external exposures impact cancer risk and progression. The integration of epigenetics into cancer research not only enhances our understanding of the disease but also opens innovative avenues for intervention that were previously unexplored in traditional genetic-focused studies. Technologies like advanced sequencing and precise epigenetic modification are paving the way for early cancer detection and more personalized treatment approaches, highlighting the critical role of epigenetics in modern cancer care.

Cancer treatment with biosimilar drugs: A review

Biosimilars are biological drugs created from living organisms or that contain living components. They share an identical amino-acid sequence and immunogenicity. These drugs are considered to be cost-effective and are utilized in the treatment of cancer and other endocrine disorders. The primary aim of biosimilars is to predict biosimilarity, efficacy, and treatment costs; they are approved by the Food and Drug Administration (FDA) and have no clinical implications. They involve analytical studies to understand the similarities and dissimilarities. A biosimilar manufacturer sets up FDA-approved reference products to evaluate biosimilarity. The contribution of next-generation sequencing is evolving to study the organ tumor and its progression with its impactful therapeutic approach on cancer patients to showcase and target rare mutations. The study shall help to understand the future perspectives of biosimilars for use in gastro-entero-logic diseases, colorectal cancer, and thyroid cancer. They also help target specific organs with essential mutational categories and drug prototypes in clinical practices with blood and liquid biopsy, cell treatment, gene therapy, recombinant therapeutic proteins, and personalized medications. Biosimilar derivatives such as monoclonal antibodies like trastuzumab and rituximab are common drugs used in cancer therapy. Escherichia coli produces more than six antibodies or antibody-derived proteins to treat cancer such as filgrastim, epoetin alfa, and so on.

Genomic characterization of peritoneal lavage cytology-positive gastric cancer

Objective

Positive peritoneal lavege cytology (CY1) gastric cancer is featured by dismal prognosis, with high risks of peritoneal metastasis. However, there is a lack of evidence on pathogenic mechanism and signature of CY1 and there is a continuous debate on CY1 therapy. Therefore, exploring the mechanism of CY1 is crucial for treatment strategies and targets for CY1 gastric cancer.

Methods

In order to figure out specific driver genes and marker genes of CY1 gastric cancer, and ultimately offer clues for potential marker and risk assessment of CY1, 17 cytology-positive gastric cancer patients and 31 matched cytology-negative gastric cancer patients were enrolled in this study. The enrollment criteria were based on the results of diagnostic laparoscopy staging and cytology inspection of exfoliated cells. Whole exome sequencing was then performed on tumor samples to evaluate genomic characterization of cytology-positive gastric cancer.

Results

Least absolute shrinkage and selection operator (LASSO) algorithm identified 43 cytology-positive marker genes, while MutSigCV identified 42 cytology-positive specific driver genes. CD3G and CDKL2 were both driver and marker genes of CY1. Regarding mutational signatures, driver gene mutation and tumor subclone architecture, no significant differences were observed between CY1 and negative peritoneal lavege cytology (CY0).

Conclusions

There might not be distinct differences between CY1 and CY0, and CY1 might represent the progression of CY0 gastric cancer rather than constituting an independent subtype. This genomic analysis will thus provide key molecular insights into CY1, which may have a direct effect on treatment recommendations for CY1 and CY0 patients, and provides opportunities for genome-guided clinical trials and drug development.

Exploring the Role of Non-synonymous and Deleterious Variants Identified in Colorectal Cancer: A Multi-dimensional Computational Scrutiny of Exomes

Introduction

Colorectal cancers are the world's third most commonly diagnosed type of cancer. Currently, there are several diagnostic and treatment options to combat it. However, a delay in detection of the disease is life-threatening. Additionally, a thorough analysis of the exomes of cancers reveals potential variation data that can be used for early disease prognosis.

Methods

By utilizing a comprehensive computational investigation, the present study aimed to reveal mutations that could potentially predispose to colorectal cancer. Ten colorectal cancer exomes were retrieved. Quality control assessments were performed using FastQC and MultiQC, gapped alignment to the human reference genome (hg19) using Bowtie2 and calling the germline variants using Haplotype caller in the GATK pipeline. The variants were filtered and annotated using SIFT and PolyPhen2 successfully categorized the mutations into synonymous, non-synonymous, start loss and stop gain mutations as well as marked them as possibly damaging, probably damaging and benign. This mutational profile helped in shortlisting frequently occurring mutations and associated genes, for which the downstream multi-dimensional expression analyses were carried out.

Results

Our work involved prioritizing the non-synonymous, deleterious SNPs since these polymorphisms bring about a functional alteration to the phenotype. The top variations associated with their genes with the highest frequency of occurrence included LGALS8, CTSB, RAD17, CPNE1, OPRM1, SEMA4D, MUC4, PDE4DIP, ELN and ADRA1A. An in-depth multi-dimensional downstream analysis of all these genes in terms of gene expression profiling and analysis and differential gene expression with regard to various cancer types revealed CTSB and CPNE1 as highly expressed and overregulated genes in colorectal cancer.

Conclusion

Our work provides insights into the various alterations that might possibly lead to colorectal cancer and suggests the possibility of utilizing the most important genes identified for wet-lab experimentation.

Actionable mutational profiling in solid tumors using hybrid-capture-based next-generation sequencing in a real-world setting in Spain

OBJECTIVE

This study aimed to describe the performance of a next-generation sequencing (NGS) panel for the detection of precise genomic alterations in cancer in Spanish clinical practice. The impact of tumor characteristics was evaluated on informative NGS and actionable mutation rates.

MATERIALS AND METHODS

A cross-sectional study was conducted at the Fundación Jiménez Díaz University Hospital (May 2021-March 2022) where molecular diagnostic of 537 Formalin-Fixed Paraffin-Embedded (FFPE) tissue samples of diverse solid tumors (lung, colorectal, melanoma, gastrointestinal stromal, among others) was performed using AVENIO Tumor Tissue Targeted Kit. A descriptive analysis of the features of all samples was carried out. Multivariable logistic analysis was conducted to assess the impact of sample characteristics on NGS performance defined by informative results rate (for all tumors and for lung tumors), and on actionable mutations rate (for lung tumors only).

RESULTS

AVENIO performance rate was 75.2% in all tumor samples and 75.3% in lung cancer samples, and the multivariable analysis showed that surgical specimens are most likely to provide informative results than diagnostic biopsies. Regarding the mutational findings, 727 pathogenic, likely pathogenic, or variant of unknown significance mutations were found in all tumor samples. Single nucleotide variant was the most common genomic alteration, both for all tumor samples (85.3% and 81.9% for all solid tumors and lung samples, respectively). In lung tumors, multivariable analysis showed that it is more likely to find actionable mutations from non-smokers and patients with adenocarcinoma, large cell, or undifferentiated histologies.

CONCLUSION

This is the largest cohort-level study in Spain to profile the analyses of biopsy samples of different tumors using NGS in routine clinical practice. Our findings showed that the use of NGS routinely provides good rates of informative results and can improve tumor characterization and identify a greater number of actionable mutations.

Concordance analysis of cerebrospinal fluid with the tumor tissue for integrated diagnosis in gliomas based on next-generation sequencing

Purpose: The driver mutations of gliomas have been identified in cerebrospinal fluid (CSF). Here we compared the concordance between CSF and tumor tissue for integrated diagnosis in gliomas using next-generation sequencing (NGS) to evaluate the feasibility of CSF detection in gliomas. Patients and methods: 27 paired CSF/tumor tissues of glioma patients were sequenced by a customized gene panel based on NGS. All CSF samples were collected through lumbar puncture before surgery. Integrated diagnosis was made by analysis of histology and tumor DNA molecular pathology according to the 2021 WHO classification of the central nervous system tumors. Results: A total of 24 patients had detectable circulating tumor DNA (ctDNA) and 22 had at least one somatic mutation or chromosome alteration in CSF. The ctDNA levels varied significantly across different ages, Ki-67 index, magnetic resonance imaging signal and glioma subtypes (p < 0.05). The concordance between integrated ctDNA diagnosis and the final diagnosis came up to 91.6% (Kappa, 0.800). We reclassified the clinical diagnosis of 3 patients based on the results of CSF ctDNA sequencing, and 4 patients were reassessed depending on tumor DNA. Interestingly, a rare IDH1 R132C was identified in CSF ctDNA, but not in the corresponding tumor sample. Conclusion: This study demonstrates a high concordance between integrated ctDNA diagnosis and the final diagnosis of gliomas, highlighting the practicability of NGS based detection of mutations of CSF in assisting integrated diagnosis of gliomas, especially glioblastoma.

MicroRNA targeting: A novel therapeutic intervention for ovarian cancer

Ovarian cancer, a perilous form of cancer affecting the female reproductive system, exhibits intricate communication networks that contribute to its progression. This study aims to identify crucial molecular abnormalities linked to the disease to enhance diagnostic and therapeutic strategies. In particular, we investigate the role of microRNAs (miRNAs) as diagnostic biomarkers and explore their potential in treating ovarian cancer. By targeting miRNAs, which can influence multiple pathways and genes, substantial therapeutic benefits can be attained. In this review we want to shed light on the promising application of miRNA-based interventions and provide insights into the specific miRNAs implicated in ovarian cancer pathogenesis.

Histology Specific Molecular Biomarkers: Ushering in a New Era of Precision Radiation Oncology

Histopathology and clinical staging have historically formed the backbone for allocation of treatment decisions in oncology. Although this has provided an extremely practical and fruitful approach for decades, it has long been evident that these data alone do not adequately capture the heterogeneity and breadth of disease trajectories experienced by patients. As efficient and affordable DNA and RNA sequencing have become available, the ability to provide precision therapy has become within grasp. This has been realized with systemic oncologic therapy, as targeted therapies have demonstrated immense promise for subsets of patients with oncogene-driver mutations. Further, several studies have evaluated predictive biomarkers for response to systemic therapy within a variety of malignancies. Within radiation oncology, the use of genomics/transcriptomics to guide the use, dose, and fractionation of radiation therapy is rapidly evolving but still in its infancy. The genomic adjusted radiation dose/radiation sensitivity index is one such early and exciting effort to provide genomically guided radiation dosing with a pan-cancer approach. In addition to this broad method, a histology specific approach to precision radiation therapy is also underway. Herein we review select literature surrounding the use of histology specific, molecular biomarkers to allow for precision radiotherapy with the greatest emphasis on commercially available and prospectively validated biomarkers.

Diagnosis of invasive fungal infections: challenges and recent developments

BACKGROUND

The global burden of invasive fungal infections (IFIs) has shown an upsurge in recent years due to the higher load of immunocompromised patients suffering from various diseases. The role of early and accurate diagnosis in the aggressive containment of the fungal infection at the initial stages becomes crucial thus, preventing the development of a life-threatening situation. With the changing demands of clinical mycology, the field of fungal diagnostics has evolved and come a long way from traditional methods of microscopy and culturing to more advanced non-culture-based tools. With the advent of more powerful approaches such as novel PCR assays, T2 Candida, microfluidic chip technology, next generation sequencing, new generation biosensors, nanotechnology-based tools, artificial intelligence-based models, the face of fungal diagnostics is constantly changing for the better. All these advances have been reviewed here giving the latest update to our readers in the most orderly flow.

MAIN TEXT

A detailed literature survey was conducted by the team followed by data collection, pertinent data extraction, in-depth analysis, and composing the various sub-sections and the final review. The review is unique in its kind as it discusses the advances in molecular methods; advances in serology-based methods; advances in biosensor technology; and advances in machine learning-based models, all under one roof. To the best of our knowledge, there has been no review covering all of these fields (especially biosensor technology and machine learning using artificial intelligence) with relevance to invasive fungal infections.

CONCLUSION

The review will undoubtedly assist in updating the scientific community's understanding of the most recent advancements that are on the horizon and that may be implemented as adjuncts to the traditional diagnostic algorithms.

Experimental Models for Rare Melanoma Research-The Niche That Needs to Be Addressed

Melanoma, the tumor arising from the malignant transformation of pigment-producing cells-the melanocytes-represents one of the most severe cancer types. Despite their rarity compared to cutaneous melanoma, the extracutaneous subtypes such as uveal melanoma (UM), acral lentiginous melanoma (ALM), and mucosal melanoma (MM) stand out due to their increased aggressiveness and mortality rate, demanding continuous research to elucidate their specific pathological features and develop efficient therapies. Driven by the emerging progresses made in the preclinical modeling of melanoma, the current paper covers the most relevant in vitro, in vivo, and in ovo systems, providing a deeper understanding of these rare melanoma subtypes. However, the preclinical models for UM, ALM, and MM that were developed so far remain scarce, and none of them is able to completely simulate the complexity that is characteristic to these melanomas; thus, a continuous expansion of the existing library of experimental models is pivotal for driving advancements in this research field. An overview of the applicability of precision medicine in the management of rare melanoma subtypes is also provided.

Towards Understanding the Key Signature Pathways Associated from Differentially Expressed Gene Analysis in an Indian Prostate Cancer Cohort

Prostate cancer (PCa) is one of the most prevalent cancers among men in India. Although studies on PCa have dealt with genetics, genomics, and the environmental influence in the causality of PCa, not many studies employing the Next Generation Sequencing (NGS) approaches of PCa have been carried out. In our previous study, we identified some causal genes and mutations specific to Indian PCa using Whole Exome Sequencing (WES). In the recent past, with the help of different cancer consortiums such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), along with differentially expressed genes (DEGs), many cancer-associated novel non-coding RNAs have been identified as biomarkers. In this work, we attempt to identify differentially expressed genes (DEGs) including long non-coding RNAs (lncRNAs) associated with signature pathways from an Indian PCa cohort using the RNA-sequencing (RNA-seq) approach. From a cohort of 60, we screened six patients who underwent prostatectomy; we performed whole transcriptome shotgun sequencing (WTSS)/RNA-sequencing to decipher the DEGs. We further normalized the read counts using fragments per kilobase of transcript per million mapped reads (FPKM) and analyzed the DEGs using a cohort of downstream regulatory tools, viz., GeneMANIA, Stringdb, Cytoscape-Cytohubba, and cbioportal, to map the inherent signatures associated with PCa. By comparing the RNA-seq data obtained from the pairs of normal and PCa tissue samples using our benchmarked in-house cuffdiff pipeline, we observed some important genes specific to PCa, such as STEAP2, APP, PMEPA1, PABPC1, NFE2L2, and HN1L, and some other important genes known to be involved in different cancer pathways, such as COL6A1, DOK5, STX6, BCAS1, BACE1, BACE2, LMOD1, SNX9, CTNND1, etc. We also identified a few novel lncRNAs such as LINC01440, SOX2OT, ENSG00000232855, ENSG00000287903, and ENST00000647843.1 that need to be characterized further. In comparison with publicly available datasets, we have identified characteristic DEGs and novel lncRNAs implicated in signature PCa pathways in an Indian PCa cohort which perhaps have not been reported. This has set a precedent for us to validate candidates further experimentally, and we firmly believe this will pave a way toward the discovery of biomarkers and the development of novel therapies.

Targeted therapies in non-small cell lung cancer and the potential role of AI interventions in cancer treatment

Non-small cell lung cancer is the most prevalent lung cancer, and almost three-fourths of patients are diagnosed in the advanced stage directly. In this stage, chemotherapy gives only a 15% 5-year survival rate. As people have varied symptoms and reactions to a specific cancer type, treatment for the tumor is likely to fall short, complicating cancer therapy. Immunotherapy is a breakthrough treatment involving drugs targeting novel immune checkpoint inhibitors like CTLA-4 and PD-1/PD-L1, along with combination therapies. In addition, the utility of engineered CAR-T and CAR-NK cells can be an effective strategy to promote the immune response against tumors. The concept of personalized cancer vaccines with the discovery of neoantigens loaded on dendritic cell vectors can also be an effective approach to cure cancer. Advances in genetic engineering tools like CRISPR/Cas9-mediated gene editing of T cells to enhance their effector function is another ray of hope. This review aims to provide an overview of recent developments in cancer immunotherapy, which can be used in first- and second-line treatments in the clinical space. Further, the intervention of artificial intelligence to detect cancer tumors at an initial stage with the help of machine learning techniques is also explored.

Pharmacogenetics of Anticancer Drugs: Clinical Response and Toxicity

Cancer is the most challenging disease for medical professionals to treat. The factors underlying the complicated situation include anticancer drug-associated toxicity, non-specific response, low therapeutic window, variable treatment outcomes, development of drug resistance, treatment complications, and cancer recurrence. The remarkable advancement in biomedical sciences and genetics, over the past few decades, however, is changing the dire situation. The discovery of gene polymorphism, gene expression, biomarkers, particular molecular targets and pathways, and drug-metabolizing enzymes have paved the way for the development and provision of targeted and individualized anticancer treatment. Pharmacogenetics is the study of genetic factors having the potential to affect clinical responses and pharmacokinetic and pharmacodynamic behaviors of drugs. This chapter emphasizes pharmacogenetics of anticancer drugs and its applications in improving treatment outcomes, selectivity, toxicity of the drugs, and discovering and developing personalized anticancer drugs and genetic methods for prediction of drug response and toxicity.

Circulating tumor DNA tracking in patients with pancreatic cancer using next-generation sequencing

BACKGROUND

Pancreatic cancer remains one of the most devastating malignancies due to the absence of techniques for early diagnosis and the lack of target therapeutic options for advanced disease. Next Generation Sequencing (NGS) generates high throughput and valuable genetic information when evaluating circulating tumor DNA (ctDNA); however clinical utility of liquid biopsy in pancreatic cancer has not been demonstrated yet. The aim of this study was to evaluate whether results from a Next Generation Sequencing panel on plasma samples from pancreatic cancer patients could have a clinical significance.

METHODS

From December 2016 to January 2020, plasma samples from 27 patients with pancreatic ductal adenocarcinoma at two different tertiary Spanish Hospitals underwent ctDNA testing using a commercial NGS panel of 65 genes. Clinical data were available for these patients. VarsSome Clinical software was used to analyse NGS data and establish pathogenicity.

RESULTS

Evaluable NGS results were obtained in 18 out of the 27 plasma samples. Somatic pathogenic mutations were found mainly in KRAS, BRCA2, FLT3 and HNF1A, genes. Pathogenic mutations were detected in 50% of plasma samples from patient diagnosed at stages III-IV samples. FLT3 mutations were observed in 22.22% of samples which constitute a novel result in the field.

CONCLUSIONS

Liquid biopsy using NGS is a valuable tool but still not sensitive or specific enough to provide clinical utility in pancreatic cancer patients.

Identification of therapeutically potential targets and their ligands for the treatment of OSCC

Recent advancements in cancer biology have revealed molecular changes associated with carcinogenesis and chemotherapeutic exposure. The available information is being gainfully utilized to develop therapies targeting specific molecules involved in cancer cell growth, survival, and chemoresistance. Targeted therapies have dramatically increased overall survival (OS) in many cancers. Therefore, developing such targeted therapies against oral squamous cell carcinoma (OSCC) is anticipated to have significant clinical implications. In the current work, we have identified drug-specific sensitivity-related prognostic biomarkers (BOP1, CCNA2, CKS2, PLAU, and SERPINE1) using gene expression, Cox proportional hazards regression, and machine learning in OSCC. Dysregulation of these markers is significantly associated with OS in many cancers. Their elevated expression is related to cellular proliferation and aggressive malignancy in various cancers. Mechanistically, inhibition of these biomarkers should significantly reduce cellular proliferation and metastasis in OSCC and should result in better OS. It is pertinent to note that no effective small-molecule candidate has been identified against these biomarkers to date. Therefore, a comprehensive in silico drug design strategy assimilating homology modeling, extensive molecular dynamics (MD) simulation, and ensemble molecular docking has been applied to identify potential compounds against identified targets, and potential molecules have been identified. We hope that this study will help in deciphering potential genes having roles in chemoresistance and a significant impact on OS. It will also result in the identification of new targeted therapeutics against OSCC.

Evaluation of the Available Variant Calling Tools for Oxford Nanopore Sequencing in Breast Cancer

The goal of biomarker testing, in the field of personalized medicine, is to guide treatments to achieve the best possible results for each patient. The accurate and reliable identification of everyone’s genome variants is essential for the success of clinical genomics, employing third-generation sequencing. Different variant calling techniques have been used and recommended by both Oxford Nanopore Technologies (ONT) and Nanopore communities. A thorough examination of the variant callers might give critical guidance for third-generation sequencing-based clinical genomics. In this study, two reference genome sample datasets (NA12878) and (NA24385) and the set of high-confidence variant calls provided by the Genome in a Bottle (GIAB) were used to allow the evaluation of the performance of six variant calling tools, including Human-SNP-wf, Clair3, Clair, NanoCaller, Longshot, and Medaka, as an integral step in the in-house variant detection workflow. Out of the six variant callers understudy, Clair3 and Human-SNP-wf that has Clair3 incorporated into it achieved the highest performance rates in comparison to the other variant callers. Evaluation of the results for the tool was expressed in terms of Precision, Recall, and F1-score using Hap.py tools for the comparison. In conclusion, our findings give important insights for identifying accurate variants from third-generation sequencing of personal genomes using different variant detection tools available for long-read sequencing.

Genomic biomarkers to guide precision radiotherapy in prostate cancer

Our ability to prognosticate the clinical course of patients with cancer has historically been limited to clinical, histopathological, and radiographic features. It has long been clear however, that these data alone do not adequately capture the heterogeneity and breadth of disease trajectories experienced by patients. The advent of efficient genomic sequencing has led to a revolution in cancer care as we try to understand and personalize treatment specific to patient clinico-genomic phenotypes. Within prostate cancer, emerging evidence suggests that tumor genomics (e.g., DNA, RNA, and epigenetics) can be utilized to inform clinical decision making. In addition to providing discriminatory information about prognosis, it is likely tumor genomics also hold a key in predicting response to oncologic therapies which could be used to further tailor treatment recommendations. Herein we review select literature surrounding the use of tumor genomics within the management of prostate cancer, specifically leaning toward analytically validated and clinically tested genomic biomarkers utilized in radiotherapy and/or adjunctive therapies given with radiotherapy.

Duplex sequencing identifies genomic features that determine susceptibility to benzo(a)pyrene-induced in vivo mutations

Exposure to environmental mutagens increases the risk of cancer and genetic disorders. We used Duplex Sequencing (DS), a high-accuracy error-corrected sequencing technology, to analyze mutation induction across twenty 2.4 kb intergenic and genic targets in the bone marrow of MutaMouse males exposed to benzo(a)pyrene (BaP), a widespread environmental pollutant. DS revealed a linear dose-related induction of mutations across all targets with low intra-group variability. Heterochromatic and intergenic regions exhibited the highest mutation frequencies (MF). C:G > A:T transversions at CCA, CCC and GCC trinucleotides were enriched in BaP-exposed mice consistent with the known etiology of BaP mutagenesis. However, GC-content had no effect on mutation susceptibility. A positive correlation was observed between DS and the “gold-standard” transgenic rodent gene mutation assay. Overall, we demonstrate that DS is a promising approach to study in vivo mutagenesis and yields critical insight into the genomic features governing mutation susceptibility, spectrum, and variability across the genome.

Promoting Best Practice in Cancer Care in Sub Saharan Africa

Promoting best practice in the management of a cancer patient is rooted in the application of new knowledge derived through various sources including population science, laboratory advances, and translational research. Ultimately, the impact of these advances depends on their application at the patient's bedside. A close collaboration between the oncologist and the pathologist is critical in underwriting progress in the management of the cancer patient. Recent advancements have shown that more granular characteristics of the tumor and the microenvironment are defining determinants when it comes to disease course and overall outcome. Whereas, histologic features and basic immunohistochemical characterization were previously adequate to define the tumor and establish treatment recommendation, the growing capability of the pathologist to provide molecular characterization of the tumor and its microenvironment, as well as, the availability of novel therapeutic agents have revolutionized cancer treatment paradigms and improved patient-outcomes and survival. While such capacity and capability appear readily available in most developed high-income countries (HIC), it will take a concerted and collaborative effort of all stakeholders to pave the way in the same stride in the low and middle-income countries (LMIC), which bear a disproportionate burden of human illness and cancers. Patients in the LMIC present with disease at advanced stage and often display characteristics unlike those encountered in the developed world. To keep stride and avoid the disenfranchisement of patients in the LMIC will require greater participation of LMIC patients on the global clinical trial platform, and a more equitable and affordable sharing of diagnostic and therapeutic capabilities between the developed and developing world. Key to the success of this progress and improvement of patient outcomes in the developing world is the close collaboration between the oncologist and the pathologist in this new era of precision and personalized medicine.

A Targeted Next-Generation Sequencing Panel to Genotype Gliomas

Gliomas account for the majority of primary brain tumors. Glioblastoma is the most common and malignant type. Based on their extreme molecular heterogeneity, molecular markers can be used to classify gliomas and stratify patients into diagnostic, prognostic, and therapeutic clusters. In this work, we developed and validated a targeted next-generation sequencing (NGS) approach to analyze variants or chromosomal aberrations correlated with tumorigenesis and response to treatment in gliomas. Our targeted NGS analysis covered 13 glioma-related genes (ACVR1, ATRX, BRAF, CDKN2A, EGFR, H3F3A, HIST1H3B, HIST1H3C, IDH1, IDH2, P53, PDGFRA, PTEN), a 125 bp region of the TERT promoter, and 54 single nucleotide polymorphisms (SNPs) along chromosomes 1 and 19 for reliable assessment of their copy number alterations (CNAs). Our targeted NGS approach provided a portrait of gliomas’ molecular heterogeneity with high accuracy, specificity, and sensitivity in a single workflow, enabling the detection of variants associated with unfavorable outcomes, disease progression, and drug resistance. These preliminary results support its use in routine diagnostic neuropathology.

Reverse Electrochemical Sensing of FLT3-ITD Mutations in Acute Myeloid Leukemia Using Gold Sputtered ZnO-Nanorod Configured DNA Biosensors

Detection of genetic mutations leading to hematological malignancies is a key factor in the early diagnosis of acute myeloid leukemia (AML). FLT3-ITD mutations are an alarming gene defect found commonly in AML patients associated with high cases of leukemia and low survival rates. Available diagnostic assessments for FLT3-ITD are incapable of combining cost-effective detection platforms with high analytical performances. To circumvent this, we developed an efficient DNA biosensor for the recognition of AML caused by FLT3-ITD mutation utilizing electrochemical impedance characterization. The system was designed by adhering gold-sputtered zinc oxide (ZnO) nanorods onto interdigitated electrode (IDE) sensor chips. The sensing surface was biointerfaced with capture probes designed to hybridize with unmutated FLT3 sequences instead of the mutated FLT3-ITD gene, establishing a reverse manner of target detection. The developed biosensor demonstrated specific detection of mutated FLT3 genes, with high levels of sensitivity in response to analyte concentrations as low as 1 nM. The sensor also exhibited a stable functional life span of more than five weeks with good reproducibility and high discriminatory properties against FLT3 gene targets. Hence, the developed sensor is a promising tool for rapid and low-cost diagnostic applications relevant to the clinical prognosis of AML stemming from FLT3-ITD mutations.

Implementation of Early Next-Generation Sequencing for Inborn Errors of Immunity: A Prospective Observational Cohort Study of Diagnostic Yield and Clinical Implications in Dutch Genome Diagnostic Centers

Objective

Inborn errors of immunity (IEI) are a heterogeneous group of disorders, affecting different components of the immune system. Over 450 IEI related genes have been identified, with new genes continually being recognized. This makes the early application of next-generation sequencing (NGS) as a diagnostic method in the evaluation of IEI a promising development. We aimed to provide an overview of the diagnostic yield and time to diagnosis in a cohort of patients suspected of IEI and evaluated by an NGS based IEI panel early in the diagnostic trajectory in a multicenter setting in the Netherlands.

Study Design

We performed a prospective observational cohort study. We collected data of 165 patients with a clinical suspicion of IEI without prior NGS based panel evaluation that were referred for early NGS using a uniform IEI gene panel. The diagnostic yield was assessed in terms of definitive genetic diagnoses, inconclusive diagnoses and patients without abnormalities in the IEI gene panel. We also assessed time to diagnosis and clinical implications.

Results

For children, the median time from first consultation to diagnosis was 119 days versus 124 days for adult patients (U=2323; p=0.644). The median turn-around time (TAT) of genetic testing was 56 days in pediatric patients and 60 days in adult patients (U=1892; p=0.191). A definitive molecular diagnosis was made in 25/65 (24.6%) of pediatric patients and 9/100 (9%) of adults. Most diagnosed disorders were identified in the categories of immune dysregulation (n=10/25; 40%), antibody deficiencies (n=5/25; 20%), and phagocyte diseases (n=5/25; 20%). Inconclusive outcomes were found in 76/165 (46.1%) patients. Within the patient group with a genetic diagnosis, a change in disease management occurred in 76% of patients.

Conclusion

In this cohort, the highest yields of NGS based evaluation for IEI early in the diagnostic trajectory were found in pediatric patients, and in the disease categories immune dysregulation and phagocyte diseases. In cases where a definitive diagnosis was made, this led to important disease management implications in a large majority of patients. More research is needed to establish a uniform diagnostic pathway for cases with inconclusive diagnoses, including variants of unknown significance.

Current Trends in Precision Medicine and Next-Generation Sequencing in Head and Neck Cancer

OPINION STATEMENT

As the field of oncology enters the era of precision medicine and targeted therapies, we have come to realize that there may be no single "magic bullet" for patients with head and neck cancer. While immune check point inhibitors and some targeted therapeutics have shown great promise in improving oncologic outcomes, the current standard of care in most patients with head and neck squamous cell carcinoma (HNSCC) remains a combination of surgery, radiation, and/or cytotoxic chemotherapy. Nevertheless, advances in precision medicine, next-generation sequencing (NGS), and targeted therapies have a potential future in the treatment of HNSCC. These roles include increased patient treatment stratification based on predictive biomarkers or targetable mutations and novel combinatorial regimens with existing HNSCC treatments. There remain challenges to precision medicine and NGS in HNSCC, including intertumor and intratumor heterogeneity, challenging targets, and need for further trials validating the utility of NGS and precision medicine. Additionally, there is a need for evidence-based practice guidelines to assist clinicians on how to appropriately incorporate NGS in care for HNSCC. In this review, we describe the current state of precision medicine and NGS in HNSCC and opportunities for future advances in this challenging but important field.

Incidental germline findings during molecular profiling of tumor tissues for precision oncology: molecular survey and methodological obstacles

Background

A fraction of patients referred for complex molecular profiling of biopsied tumors may harbor germline variants in genes associated with the development of hereditary cancer syndromes (HCS). Neither the bioinformatic analysis nor the reporting of such incidental germline findings are standardized.

Methods

Data from Next-Generation Sequencing (NGS) of biopsied tumor samples referred for complex molecular profiling were analyzed for germline variants in HCS-associated genes. Analysis of variant origin was performed employing bioinformatic algorithms followed by manual curation. When possible, the origin of the variant was validated by Sanger sequencing of the sample of normal tissue. The variants’ pathogenicity was assessed according to ACMG/AMP.

Results

Tumors were sampled from 183 patients (Males: 75 [41.0%]; Females: 108 [59.0%]; mean [SD] age, 57.7 [13.3] years) and analysed by targeted NGS. The most common tumor types were colorectal (19%), pancreatic (13%), and lung cancer (10%). A total of 56 sequence variants in genes associated with HCS were detected in 40 patients. Of them, 17 variants found in 14 patients were predicted to be of germline origin, with 6 variants interpreted as pathogenic (PV) or likely pathogenic (LPV), and 9 as variants of uncertain significance (VUS). For the 41 out of 42 (97%) missense variants in HCS-associated genes, the results of computational prediction of variant origin were concordant with that of experimental examination. We estimate that Sanger sequencing of a sample of normal tissue would be required for ~ 1–7% of the total assessed cases with PV or LPV, when necessity to follow with genetic counselling referral in ~ 2–15% of total assessed cases (PV, LPV or VUS found in HCS genes).

Conclusion

Incidental findings of pathogenic germline variants are common in data from cancer patients referred for complex molecular profiling. We propose an algorithm for the management of patients with newly detected variants in genes associated with HCS.

Undifferentiated Pleomorphic Sarcoma Presenting With Cardiac Tamponade: A Case Report and Review

Soft tissue sarcomas (STS) comprise a large group of heterogeneous malignant tumors that form approximately 1% of all adult malignancies. Most sarcomas originate from soft tissue and the rest arise from the bone. Undifferentiated pleomorphic sarcoma (UPS) is an aggressive tumor that usually presents as an asymptomatic subcutaneous mass that exhibits rapid growth with unremarkable skin findings. The diagnosis is usually made with histopathology or immunohistochemistry; once the diagnosis is confirmed, evaluation and workup of the primary tumor, lymph nodes, and metastasis should be made. Treatment is stage-dependent but generally involves en-bloc resection followed by a review of pathology with a discussion of the benefits of adjuvant radiation or chemotherapy. Here, we discuss a case of a 77-year-old patient who presented with a large mass over the right shoulder and echocardiographic findings of cardiac tamponade.

Establishing Novel Molecular Subtypes of Appendiceal Cancer

PURPOSE

Appendiceal cancer is a rare disease process with complex treatment strategies. The objective of this study was to identify mutation-based genetic subtypes that may differ from the current histological classification, compare the genetic make-up of primaries and metastases, and find novel targetable alterations.

METHODS

The analyses involved the curation and normalization of gene mutation panels from appendiceal adenocarcinoma and mucinous adenocarcinoma (n = 196) stored in the AACR GENIE Database v6.0. Genes mutated in less than one patient and tumors profiled with incomplete mutation panels were excluded from the study. The optimal number of AC subtypes was established using the Nonnegative Matrix Factorization algorithm. Statistical comparisons of mutation frequencies were performed using Pearson's χ² test.

RESULTS

AC patients were stratified into five mutation subtypes, based on a final set of 41 cancer-related genes. AC0 had no mutations. The most frequently mutated genes varied between the subtypes were: AC1: KRAS (91.9%) and GNAS (77.4%); AC2: KRAS (52.5%), APC (32.5%), and GNAS (30%); AC3: KMT2D (38.7%), TP53 (38.7%), KRAS (35.5%), EP300 (22.6%); and AC4: TP53 (97.2%), KRAS (77.8%), and SMAD4 (36.1%). Additionally, AC3 was less likely to be mucinous (22.6% vs. 50.0-74.2%, p < 0.001) and had a higher mutation frequency (3.6 vs. 0-3.1, p < 0.001). There were no significant differences between primary tumors and metastases in the 41 assessed genes (p = 0.35).

CONCLUSIONS

The characterization of these subtypes suggests a need for molecular approaches to complement anatomical and histopathological staging for AC. A prospective comparison of subtype prognosis and response to surgery and adjuvant treatment is needed to identify the clinical applications of the novel molecular subtypes.

Microfluidic Single-Cell Proteomics Assay Chip: Lung Cancer Cell Line Case Study

Cancer is a dynamic disease involving constant changes. With these changes, cancer cells become heterogeneous, resulting in varying sensitivity to chemotherapy. The heterogeneity of cancer cells plays a key role in chemotherapy resistance and cancer recurrence. Therefore, for effective treatment, cancer cells need to be analyzed at the single-cell level by monitoring various proteins and investigating their heterogeneity. We propose a microfluidic chip for a single-cell proteomics assay that is capable of analyzing complex cellular signaling systems to reveal the heterogeneity of cancer cells. The single-cell assay chip comprises (i) microchambers (n = 1376) for manipulating single cancer cells, (ii) micropumps for rapid single-cell lysis, and (iii) barcode immunosensors for detecting nine different secretory and intracellular proteins to reveal the correlation among cancer-related proteins. Using this chip, the single-cell proteomics of a lung cancer cell line, which may be easily masked in bulk analysis, were evaluated. By comparing changes in the level of protein secretion and heterogeneity in response to combinations of four anti-cancer drugs, this study suggests a new method for selecting the best combination of anti-cancer drugs. Subsequent preclinical and clinical trials should enable this platform to become applicable for patient-customized therapies.

Characteristics and Clinical Application of Extracellular Vesicle-Derived DNA

Extracellular vesicles (EVs) carry RNA, proteins, lipids, and diverse biomolecules for intercellular communication. Recent studies have reported that EVs contain double-stranded DNA (dsDNA) and oncogenic mutant DNA. The advantage of EV-derived DNA (EV DNA) over cell-free DNA (cfDNA) is the stability achieved through the encapsulation in the lipid bilayer of EVs, which protects EV DNA from degradation by external factors. The existence of DNA and its stability make EVs a useful source of biomarkers. However, fundamental research on EV DNA remains limited, and many aspects of EV DNA are poorly understood. This review examines the known characteristics of EV DNA, biogenesis of DNA-containing EVs, methylation, and next-generation sequencing (NGS) analysis using EV DNA for biomarker detection. On the basis of this knowledge, this review explores how EV DNA can be incorporated into diagnosis and prognosis in clinical settings, as well as gene transfer of EV DNA and its therapeutic potential.

Evaluating, Filtering and Clustering Genetic Disease Cohorts Based on Human Phenotype Ontology Data with Cohort Analyzer

Exhaustive and comprehensive analysis of pathological traits is essential to understanding genetic diseases, performing precise diagnosis and prescribing personalized treatments. It is particularly important for disease cohorts, as thoroughly detailed phenotypic profiles allow patients to be compared and contrasted. However, many disease cohorts contain patients that have been ascribed low numbers of very general and relatively uninformative phenotypes. We present Cohort Analyzer, a tool that measures the phenotyping quality of patient cohorts. It calculates multiple statistics to give a general overview of the cohort status in terms of the depth and breadth of phenotyping, allowing us to detect less well-phenotyped patients for re-examining or excluding from further analyses. In addition, it performs clustering analysis to find subgroups of patients that share similar phenotypic profiles. We used it to analyse three cohorts of genetic diseases patients with very different properties. We found that cohorts with the most specific and complete phenotypic characterization give more potential insights into the disease than those that were less deeply characterised by forming more informative clusters. For two of the cohorts, we also analysed genomic data related to the patients, and linked the genomic data to the patient-subgroups by mapping shared variants to genes and functions. The work highlights the need for improved phenotyping in this era of personalized medicine. The tool itself is freely available alongside a workflow to allow the analyses shown in this work to be applied to other datasets.

Factors of Endoscopic Ultrasound-Guided Tissue Acquisition for Successful Next-Generation Sequencing in Pancreatic Ductal Adenocarcinoma

Background/Aims

Recent advances in understanding the genetics of pancreatic ductal adenocarcinoma (PDAC) have led to the potential for a personalized approach. Several studies have described the feasibility of generating genetic profiles of PDAC with next-generation sequencing (NGS) of samples obtained through endoscopic ultrasound-guided tissue acquisition (EUS-TA). The aim of this study was to find the best EUS-TA approach for successful NGS of PDAC.

Methods

We attempted to perform NGS with tissues from 190 patients with histologically proven PDAC by endoscopic ultrasound-guided fine-needle aspiration and endoscopic ultrasound-guided fine-needle biopsy at Samsung Medical Center between November 2011 and February 2015. The medical records of these patients were retrospectively reviewed for parameters including tumor factors (size, location, and T stage), EUS-TA factors (needle gauge [G], needle type, and number of needle passes) and histologic factors (cellularity and blood contamination). The sample used for NGS was part of the EUS-TA specimen that underwent cytological and histological analysis.

Results

NGS could be successfully performed in 109 patients (57.4%). In the univariate analysis, a large needle G (p=0.003) and tumor located in the body/tail (p=0.005) were associated with successful NGS. The multivariate logistic regression analysis revealed that the needle G was an independent factor of successful NGS (odds ratio, 2.19; 95% confidence interval, 1.08 to 4.47; p=0.031).

Conclusions

The needle G is an independent factor associated with successful NGS. This finding may suggest that the quantity of cells obtained from EUS-TA specimens is important for successful NGS.

Complete Radiological Response of Recurrent Metastatic Adrenocortical Carcinoma to Pembrolizumab and Mitotane

Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis. Treatment options for ACC are limited, with resection the main intervention. Most cases present in late metastatic cases, and data regarding effective therapies is limited. We report a case of ACC in a 40-year-old woman with history of ACC postadrenalectomy, who presented with recurrent metastatic ACC in the left perinephric space. She was started on pembrolizumab which was added to her mitotane maintenance therapy. Complete radiological response was achieved after 4 cycles of pembrolizumab. As far as we know, this is the first case to achieve complete radiological response with mitotane and pembrolizumab in recurrent metastatic ACC, with negative prognostic markers and no prior radiotherapy. As our findings are in the setting of one clinical case, we suggest the need to perform a trial to assess the benefit of combining mitotane and pembrolizumab in treating metastatic ACC.

Functional coding/non-coding variants in EGFR, ROS1 and ALK genes and their role in liquid biopsy as a personalized therapy

Personalized medicine holds promise to tailor the treatment options for patients' unique genetic make-up, behavioral and environmental background. Liquid biopsy is non-invasive technique and precise diagnosis and treatment approach. Significantly, NGS technologies have revolutionized the genomic medicine by novel identifying SNPs, indel mutations in both coding and non-coding regions and also a promising technology to accelerate the early detection and finding new biomarkers for diagnosis and treatment. The number of the bioinformatics tools have been rapidly increasing with the aim of learning more about the detected mutations either they have a pathogenic role or not. EGFR, ROS1 and ALK genes are members of the RTK family. Until now, mutations within these genes have been associated with many cancers and involved in resistance formation to TKIs. This review article summarized the findings about the mostly investigated variations in EGFR, ROS1 and ALK genes and their potential role in liquid biopsy approach.

The vaginal microbiome of sub-Saharan African women: revealing important gaps in the era of next-generation sequencing

Accurate characterization of the vaginal microbiome remains a fundamental goal of the Human Microbiome project (HMP). For over a decade, this goal has been made possible deploying high-throughput next generation sequencing technologies (NGS), which indeed has revolutionized medical research and enabled large-scale genomic studies. The 16S rRNA marker-gene survey is the most commonly explored approach for vaginal microbial community studies. With this approach, prior studies have elucidated substantial variations in the vaginal microbiome of women from different ethnicities. This review provides a comprehensive account of studies that have deployed this approach to describe the vaginal microbiota of African women in health and disease. On the basis of published data, the few studies reported from the African population are mainly in non-pregnant post pubertal women and calls for more detailed studies in pregnant and postnatal cohorts. We provide insight on the use of more sophisticated cutting-edge technologies in characterizing the vaginal microbiome. These technologies offer high-resolution detection of vaginal microbiome variations and community functional capabilities, which can shed light into several discrepancies observed in the vaginal microbiota of African women in an African population versus women of African descent in the diaspora.

Characterization and comparison of genomic profiles between primary cancer cell lines and parent atypical meningioma tumors

Background

Meningiomas are the second most common primary tumors of the central nervous system. However, there is a paucity of data on meningioma biology due to the lack of suitable preclinical in vitro and in vivo models. In this study, we report the establishment and characterization of patient-derived, spontaneously immortalized cancer cell lines derived from World Health Organization (WHO) grade I and atypical WHO grade II meningiomas.

Methods

We evaluated high-resolution 3T MRI neuroimaging findings in meningioma patients which were followed by histological analysis. RT-qPCR and immunostaining analyses were performed to determine the expression levels of meningioma-related factors. Additionally, flow cytometry and sorting assays were conducted to investigate and isolate the CD133 and CD44 positive cells from primary atypical meningioma cells. Further, we compared the gene expression profiles of meningiomas and cell lines derived from them by performing whole-exome sequencing of the blood and tumor samples from the patients, and the primary cancer cell lines established from the meningioma tumor.

Results

Our results were consistent with earlier studies that reported mutations in NF2, SMO, and AKT1 genes in atypical meningiomas, and we also observed mutations in MYBL2, a gene that was recently discovered. Significantly, the genomic signature was consistent between the atypical meningioma cancer cell lines and the tumor and blood samples from the patient.

Conclusion

Our results lead us to conclude that established meningioma cell lines with a genomic signature identical to tumors might be a valuable tool for understanding meningioma tumor biology, and for screening therapeutic agents to treat recurrent meningiomas.

Investigation on the prognostic impact of concurrent genomic alterations in crizotinib-treated EML4-ALK-rearranged advanced non-small cell lung cancer patients

BACKGROUND

Despite the efficacy of crizotinib in non-small cell lung cancer (NSCLC) with genomic rearrangement between echinoderm microtubule-associated protein-like 4 (EML4) and anaplastic lymphoma kinase (ALK), clinical outcomes are heterogeneous among these patients. In our study, we investigated concurrent molecular factors that could contribute to the heterogeneity of their clinical outcomes to crizotinib therapy.

METHODS

We retrospectively analyzed the clinical and targeted sequencing data from 32 crizotinib-treated patients with EML4-ALK-rearranged advanced NSCLC.

RESULTS

Analysis of the mutation profile revealed the detection of concurrent deleterious mutations in 17 patients (53 %, 17/32). Of which, 5 patients had deleterious copy number variations and 12 patients had deleterious single nucleotide variations. Seven patients did not harbor any concurrent mutations from the genes included in the panel. The remaining 8 patients harbored concurrent mutations which were either non-deleterious or variants of uncertain significance. TP53, detected from 34 % (11/32) of the patients and the most commonly co-occurring mutation in our cohort, was not significantly associated with survival outcomes. Interestingly, significantly shorter progression-free survival (P = 0.032) was observed in patients harboring concurrent deleterious mutations, particularly copy number amplifications (PFS, P = 0.0021; OS, P = 0.034), than those without concurrent deleterious mutations. Harboring more copy number variations, reflected by chromosomal fluctuation coefficient varscore, was associated with shorter progression-free survival (P = 0.02).

CONCLUSION

Our study revealed that concurrent deleterious mutations, particularly copy number amplifications in oncogenic genes have prognostic implications in patients with EML4-ALK-rearranged NSCLC receiving crizotinib therapy. These observations advance the understanding of the heterogeneity of treatment responses among patients with EML4-ALK-rearranged tumors.

A decision tree to improve identification of pathogenic mutations in clinical practice

BACKGROUND

A variant of unknown significance (VUS) is a variant form of a gene that has been identified through genetic testing, but whose significance to the organism function is not known. An actual challenge in precision medicine is to precisely identify which detected mutations from a sequencing process have a suitable role in the treatment or diagnosis of a disease. The average accuracy of pathogenicity predictors is 85%. However, there is a significant discordance about the identification of mutational impact and pathogenicity among them. Therefore, manual verification is necessary for confirming the real effect of a mutation in its casuistic.

METHODS

In this work, we use variables categorization and selection for building a decision tree model, and later we measure and compare its accuracy with four known mutation predictors and seventeen supervised machine-learning (ML) algorithms.

RESULTS

The results showed that the proposed tree reached the highest precision among all tested variables: 91% for True Neutrals, 8% for False Neutrals, 9% for False Pathogenic, and 92% for True Pathogenic.

CONCLUSIONS

The decision tree exceptionally demonstrated high classification precision with cancer data, producing consistently relevant forecasts for the sample tests with an accuracy close to the best ones achieved from supervised ML algorithms. Besides, the decision tree algorithm is easier to apply in clinical practice by non-IT experts. From the cancer research community perspective, this approach can be successfully applied as an alternative for the determination of potential pathogenicity of VOUS.

Minimal Residual Disease Detection in Acute Lymphoblastic Leukemia

Minimal residual disease (MRD) refers to a chemotherapy/radiotherapy-surviving leukemia cell population that gives rise to relapse of the disease. The detection of MRD is critical for predicting the outcome and for selecting the intensity of further treatment strategies. The development of various new diagnostic platforms, including next-generation sequencing (NGS), has introduced significant advances in the sensitivity of MRD diagnostics. Here, we review current methods to diagnose MRD through phenotypic marker patterns or differential gene patterns through analysis by flow cytometry (FCM), polymerase chain reaction (PCR), real-time quantitative polymerase chain reaction (RQ-PCR), reverse transcription polymerase chain reaction (RT-PCR) or NGS. Future advances in clinical procedures will be molded by practical feasibility and patient needs regarding greater diagnostic sensitivity.

Applications of Next Generation Sequencing to the Analysis of Familial Breast/Ovarian Cancer

Next generation sequencing (NGS) provides a powerful tool in the field of medical genetics, allowing one to perform multi-gene analysis and to sequence entire exomes (WES), transcriptomes or genomes (WGS). The generated high-throughput data are particularly suitable for enhancing the understanding of the genetic bases of complex, multi-gene diseases, such as cancer. Among the various types of tumors, those with a familial predisposition are of great interest for the isolation of novel genes or gene variants, detectable at the germline level and involved in cancer pathogenesis. The identification of novel genetic factors would have great translational value, helping clinicians in defining risk and prevention strategies. In this regard, it is known that the majority of breast/ovarian cases with familial predisposition, lacking variants in the highly penetrant BRCA1 and BRCA2 genes (non-BRCA), remains unexplained, although several less penetrant genes (e.g., ATM, PALB2) have been identified. In this scenario, NGS technologies offer a powerful tool for the discovery of novel factors involved in familial breast/ovarian cancer. In this review, we summarize and discuss the state of the art applications of NGS gene panels, WES and WGS in the context of familial breast/ovarian cancer.

Present and Future of Endoscopic Ultrasound-Guided Tissue Acquisition in Solid Pancreatic Tumors

Endoscopic ultrasound-guided tissue acquisition (EUS-TA) is a well-established method for pathological diagnosis of solid pancreatic neoplasm. It can be performed either as EUS-guided fine-needle aspiration (EUS-FNA) or EUS-guided fine-needle biopsy (EUSFNB). The incidence of adverse events related to EUS-TA is less than 1%. The factors that affect the diagnostic accuracy and specimen adequacy include the techniques used, type and size of the needle, competency of endosonographers, presence of cytopathologists/ cytotechnologists, and rapid on-site examination. EUS-TA may contribute to precision medicine through obtaining tissue samples for next-generation sequencing. The current status, several clinical issues for diagnostic yield and adverse events, and future perspectives of EUS-FNA/FNB for diagnosing pancreatic neoplasm have been discussed in this review article.

Polygenic Score × Intervention Moderation: an Application of Discrete-Time Survival Analysis to Model the Timing of First Marijuana Use Among Urban Youth

The present study examines the interaction between a polygenic score and an elementary school-based universal preventive intervention trial and its effects on a discrete-time survival analysis of time to first smoking marijuana. Research has suggested that initiation of substances is both genetically and environmentally driven (Rhee et al., Archives of general psychiatry 60:1256-1264, 2003; Verweij et al., Addiction 105:417-430, 2010). A previous work has found a significant interaction between the polygenic score and the same elementary school-based intervention with tobacco smoking (Musci et al., in press). The polygenic score reflects the contribution of multiple genes and has been shown in prior research to be predictive of smoking cessation, tobacco use, and marijuana use (Uhl et al., Molecular Psychiatry 19:50-54, 2014). Using data from a longitudinal preventive intervention study (N = 678), we examined age of first marijuana use from sixth grade to age 18. Genetic data were collected during emerging adulthood and were genotyped using the Affymetrix 6.0 microarray (N = 545). The polygenic score was computed using these data. Discrete-time survival analysis was employed to test for intervention main and interaction effects with the polygenic score. We found main effect of the polygenic score approaching significance, with the participants with higher polygenic scores reporting their first smoking marijuana at an age significantly later than controls (p = .050). We also found a significant intervention × polygenic score interaction effect at p = .003, with participants at the higher end of the polygenic score benefiting the most from the intervention in terms of delayed age of first use. These results suggest that genetics may play an important role in the age of first use of marijuana and that differences in genetics may account for the differential effectiveness of classroom-based interventions in delaying substance use experimentation.

Assessment of intra-tumoural colorectal cancer prognostic biomarkers using RNA in situ hybridisation

Genome-wide expression studies using microarrays and RNAseq have increased our understanding of colorectal cancer development. Translating potential gene biomarkers from these studies for clinical utility has typically relied on PCR-based technology and immunohistochemistry. Results from these techniques are limited by tumour sample heterogeneity and the lack of correlation between mRNA transcript abundance and corresponding protein levels. The aim of this research was to investigate the clinical utility of the RNA in situ hybridisation technique, RNAscope^®, for measuring intra-tumoural gene expression of potential prognostic markers in a colorectal cancer cohort. Two candidate gene markers (GFI1 and TNFRSF11A) assessed in this study were identified from a previous study led by the The Cancer Genome Atlas (TCGA) Network, and analysis was performed on 112 consecutively collected, archival FFPE colorectal cancer tumour samples. Consistent with the TCGA Network study, we found reduced GFI1 expression was associated with high-grade and left-sided tumours, and reduced TNFRSF11A expression was associated with metastasis and high nodal involvement. RNAscope^® combined with image analysis also enabled quantification of GFI1 and TNFRSF11A mRNA expression levels at the single cell level, allowing cell-type determination. These data showed that reduced mRNA transcript abundance measured in patients with poorer prognosis occurred in carcinoma cells, and not lymphocytes, stromal cells or normal epithelial cells. To our knowledge, this is the first study to assess the intra-tumoural expression patterns of GFI1 and TNFRSF11A and to validate their microarray expression profiles using RNAscope. We also demonstrate the utility of RNAscope^® technology to show that expression differences are derived from carcinoma cells rather than from cells located in the tumour microenvironment.

Heuristic value-based framework for lung cancer decision-making

Heuristics and the application of fast-and-frugal trees may play a role in establishing a clinical decision-making framework for value-based oncology. We determined whether clinical decision-making in oncology can be structured heuristically based on the timeline of the patient's treatment, clinical intuition, and evidence-based medicine. A group of 20 patients with advanced non-small cell lung cancer (NSCLC) were enrolled into the study for extensive treatment analysis and sequential decision-making. The extensive clinical and genomic data allowed us to evaluate the methodology and efficacy of fast-and-frugal trees as a way to quantify clinical decision-making. The results of the small cohort will be used to further advance the heuristic framework as a way of evaluating a large number of patients within registries. Among the cohort whose data was analyzed, substitution and amplification mutations occurred most frequently. The top five most prevalent genomic alterations were TP53 (45%), ALK (40%), LRP1B (30%), CDKN2A (25%), and MYC (25%). These 20 cases were analyzed by this clinical decision-making process and separated into two distinctions: 10 straightforward cases that represented a clearer decision-making path and 10 complex cases that represented a more intricate treatment pathway. The myriad of information from each case and their distinct pathways was applied to create the foundation of a framework for lung cancer decision-making as an aid for oncologists. In late-stage lung cancer patients, the fast-and-frugal heuristics can be utilized as a strategy of quantifying proper decision-making with limited information.

Cancer diagnostics: The journey from histomorphology to molecular profiling

Although histomorphology has made significant advances into the understanding of cancer etiology, classification and pathogenesis, it is sometimes complicated by morphologic ambiguities, and other shortcomings that necessitate the development of ancillary tests to complement its diagnostic value. A new approach to cancer patient management consists of targeting specific molecules or gene mutations in the cancer genome by inhibitory therapy. Molecular diagnostic tests and genomic profiling methods are increasingly being developed to identify tumor targeted molecular profile that is the basis of targeted therapy. Novel targeted therapy has revolutionized the treatment of gastrointestinal stromal tumor, renal cell carcinoma and other cancers that were previously difficult to treat with standard chemotherapy. In this review, we discuss the role of histomorphology in cancer diagnosis and management and the rising role of molecular profiling in targeted therapy. Molecular profiling in certain diagnostic and therapeutic difficulties may provide a practical and useful complement to histomorphology and opens new avenues for targeted therapy and alternative methods of cancer patient management.

Next-generation sequencing: recent applications to the analysis of colorectal cancer

Since the establishment of the Sanger sequencing method, scientists around the world focused their efforts to progress in the field to produce the utmost technology. The introduction of next-generation sequencing (NGS) represents a revolutionary step and promises to lead to massive improvements in our understanding on the role of nucleic acids functions. Cancer research began to use this innovative and highly performing method, and interesting results started to appear in colorectal cancer (CRC) analysis. Several studies produced high-quality data in terms of mutation discovery, especially about actionable or less frequently mutated genes, epigenetics, transcriptomics. Analysis of results is unveiling relevant perspectives aiding to evaluate the response to therapies. Novel evidences have been presented also in other directions such as gut microbiota or CRC circulating tumor cells. However, despite its unquestioned potential, NGS poses some issues calling for additional studies. This review intends to offer a view of the state of the art of NGS applications to CRC through examination of the most important technologies and discussion of recent published results.

Translating colorectal cancer genetics into clinically useful biomarkers

Colorectal cancer (CRC) is a major health problem worldwide accounting for over a million deaths annually. While many patients with Stage II and III CRC can be cured with combinations of surgery, radiotherapy and chemotherapy, this is morbid costly treatment and a significant proportion will suffer recurrence and eventually die of CRC. Increased understanding of the molecular pathogenesis of CRC has the potential to identify high risk patients and target therapy more appropriately. Despite increased understanding of the molecular events underlying CRC development, established molecular techniques have only produced a limited number of biomarkers suitable for use in routine clinical practice to predict risk, prognosis and response to treatment. Recent rapid technological developments, however, have made genomic sequencing of CRC more economical and efficient, creating potential for the discovery of genetic biomarkers that have greater diagnostic, prognostic and therapeutic capabilities for the management of CRC. This paper reviews the current understanding of the molecular pathogenesis of CRC, and summarizes molecular biomarkers that surgeons will encounter in current clinical use as well as those under development in clinical and preclinical trials. New molecular technologies are reviewed together with their potential impact on the understanding of the molecular pathogenesis of CRC and their potential clinical utility in classification, diagnosis, prognosis and targeting of therapy.