Integrating mutation variant allele frequency into clinical practice in myeloid malignancies

Integrative analyses of multi-omics data constructing tumor microenvironment and immune-related molecular prognosis model in human colorectal cancer

The increasing prevalence and incidence of colorectal cancer (CRC), particularly in young adults, underscore the imperative to comprehend its fundamental mechanisms, discover novel diagnostic and prognostic markers, and enhance therapeutic strategies. Here, we integrated multi-omics data, including gene expression, somatic mutation data and DNA methylation data, to unravel the intricacies of tumor microenvironment (TME) in CRC and search for novel prognostic markers. By calculating the immune score for each patient from the expression profile, we delineated the differential immune cell fraction, constructed an immune-related multi-omics atlas, and identified molecular characteristics. The entire colorectal dataset (n = 343) was randomly divided into training (n = 249) and testing datasets (n = 94). We screened 144 immune-related genes, 6 mutant genes, and 38 methylation probes associated with overall survival (OS). These makers were then incorporated into a 10-gene prognostic model using Lasso and Cox regression in the training dataset, and the model's performance was evaluated in an independent validation dataset. The model exhibited satisfactory results (average concordance index [C-index] = 0.77), with the average 1-year, 3-year, and 5-year AUCs being 0.79, 0.76, and 0.76 in the training dataset and 0.74, 0.80, and 0.90 in the testing dataset. Furthermore, the prognostic model demonstrated applicability in guiding chemotherapy for CRC patients and exhibited a degree of pan-cancer utility in risk stratification. In conclusion, our integrated analysis of multi-omics data revealed immune-related genetic and epigenetic characteristics of the TME. We propose an integrative prognostic model that can stratify risk and guide chemotherapy for CRC patients. The generalizability of the model in risk stratification across different cancer types was validated in Pan-Cancer cohort.

Genomic and functional impact of Trp53 inactivation in JAK2V617F myeloproliferative neoplasms

Classical myeloproliferative neoplasms (MPNs) are characterized by the proliferation of myeloid cells and the risk of transformation into myelofibrosis or acute myeloid leukemia (AML) and TP53 mutations in MPN patients are linked to AML. However, JAK2V617F has been reported to impact the TP53 response to DNA damage, suggesting potential overlapping role of TP53 inactivation in MPN. We established a mouse model showing that JAK2V617F/Vav-Cre/Trp53-/- mice displayed a similar phenotype to JAK2V617F/Vav-Cre mice, but their proliferation was outcompeted in competitive grafts. RNA-Seq revealed that half of the genes affected by JAK2V617F were affected by p53-inactivation, including the interferon pathway. To validate this finding, mice were repopulated with a mixture of wild-type and JAK2V617F (or JAK2V617F/Vav-Cre/Trp53-/-) cells and treated with pegylated interferonα. JAK2V617F-reconstituted mice entered complete hematological remission, while JAK2V617F/Vav-Cre /Trp53-/--reconstituted mice did not, confirming that p53 loss induced interferon-α resistance. KEGG and Gene Ontology analyses of common deregulated genes showed that these genes were mainly implicated in cytokine response, proliferation, and leukemia evolution, illustrating that in this mouse model, the development of MPN is not affected by TP53 inactivation. Taken together, our results show that many genetic modifications induced by JAK2V617F are influenced by TP53, the MPN phenotype may not be. Trp53 loss alone is insufficient to induce rapid leukemic transformation in steady-state hematopoiesis in JAK2V617F MPN, and Trp53 loss may contribute to interferon resistance in MPN.

Integrated variant allele frequency analysis pipeline and R package: easyVAF

Somatic sequence variants are associated with cancer diagnosis, prognostic stratification, and treatment response. Variant allele frequency (VAF), the percentage of sequence reads with a specific DNA variant over the read depth at that locus, has been used as a metric to quantify mutation rates in these applications. VAF has the potential for feature detection by reflecting changes in tumor clonal composition across treatments or time points. Although there are several packages, including Genome Analysis Toolkit and VarScan, designed for variant calling and rare mutation identification, there is no readily available package for comparing VAFs among and between groups to identify loci of interest. To this end, we have developed the R package easyVAF, which includes parametric and nonparametric tests to compare VAFs among multiple groups. It is accompanied by an interactive R Shiny app. With easyVAF, the investigator has the option between three statistical tests to maximize power while maintaining an acceptable type I error rate. This paper presents our proposed pipeline for VAF analysis, from quality checking to group comparison. We evaluate our method in a wide range of simulated scenarios and show that choosing the appropriate test to limit the type I error rate is critical. For situations where data is sparse, we recommend comparing VAFs with the beta-binomial likelihood ratio test over Fisher's exact test and Pearson's χ2 test.

Whole exome sequencing and MicroRNA profiling of lung adenocarcinoma identified risk prediction features for tumors at stage I and its substages

OBJECTIVES

About 20% of stage I lung adenocarcinoma (LUAD) patients suffer a relapse after surgical resection. While finer substages have been defined and refined in the AJCC staging system, clinical investigations on the tumor molecular landscape are lacking.

MATERIALS AND METHODS

We performed whole exome sequencing, DNA copy number and microRNA profiling on paired tumor-normal samples from a cohort of 113 treatment-naïve stage I Taiwanese LUAD patients. We searched for molecular features associated with relapse-free survival (RFS) of stage I or its substages and validated the findings with an independent Caucasian LUAD cohort.

RESULTS

We found sixteen nonsynonymous mutations harbored at EGFR, KRAS, TP53, CTNNB1 and six other genes associated with poor RFS in a dose-dependent manner via variant allele fraction (VAF). An index, maxVAF, was constructed to quantify the overall mutation load from genes other than EGFR. High maxVAF scores discriminated a small group of high-risk LUAD at stage I (median RFS: 4.5 versus 69.5 months; HR = 10.5, 95% CI = 4.22-26.12, P < 0.001). At the substage level, higher risk was found for patients with high maxVAF or high miR-31; IA (median RFS: 32.1 versus 122.8 months, P = 0.005) and IB (median RFS: 7.1 versus 26.2, P = 0.049). MicroRNAs, miR-182, miR-183 and miR-196a were found correlated with EGFR mutation and poor RFS in stage IB patients.

CONCLUSION

Distinctive features of somatic gene mutation and microRNA expression of stage I LUAD are characterized to complement the survival prognosis by substaging. The findings open up more options for precision management of stage I LUAD patients.

The clinicopathologic significance of NPM1 mutation and ability to detect mutated NPM1 by immunohistochemistry in non-AML myeloid neoplasms

NPM1 mutated non-AML myeloid neoplasms (MN; <20% blasts) are characterized by an aggressive clinical course in a few studies. In this retrospective study, we evaluate the clinicopathologic and immunohistochemical features of non-AML MN patients with NPM1 mutations. We assessed NPM1 mutation by targeted next generation sequencing (NGS). Cytoplasmic NPM1 expression was assessed by immunohistochemistry (IHC) on formalin-fixed, formic acid-decalcified bone marrow biopsy specimens. We evaluated 34 non-AML MN patients with NPM1 mutations comprising MDS (22), MPN (3) and MDS/MPN (9). They commonly presented with anemia (88%), thrombocytopenia (58%) and leukopenia (50%). Bone marrow dysplasia was common (79%). The karyotype was often normal (64%). NGS for MN-associated mutations performed in a subset of the patients showed a median of 3 mutations. NPM1 mutations were more often missense (c.859C > T p. L287F; 65%) than frameshift insertion/duplication (35%) with median variant allele frequency (VAF; 9.7%, range 5.1%-49.8%). Mutated NPM1 by IHC showed cytoplasmic positivity in 48% and positivity was associated with higher VAF. The median overall survival (OS) in this cohort was 70 months. Nine patients (26%) progressed to AML. OS in patients who progressed to AML was significantly shorter than the one of patients without progression to AML (OS 20 vs. 128 months, respectively, log rank p = 0.05). NPM1 mutated non-AML MN patients commonly had cytopenias, dysplasia, normal karyotype, mutations in multiple genes, and an unfavorable clinical outcome, including progression to AML. Our data demonstrated that IHC for NPM1 can be a useful supplementary tool to predict NPM1 mutation in some non-AML MN; however, genetic testing cannot be replaced by IHC assessment.

Effects of CALR-Mutant Type and Burden on the Phenotype of Myeloproliferative Neoplasms

Somatic CALR mutations occur in approximately 70% of patients with JAK2 V617F-negative essential thrombocythemia (ET) and primary myelofibrosis (PMF). We evaluated the effects of the CALR mutant type and burden on the phenotype of CALR-mutated myeloproliferative neoplasms (MPN). Of the 510 patients with suspected or diagnosed MPN, all 49 patients detected with CALR mutations were diagnosed with ET (n = 32) or PMF (n = 17). The CALR mutant burden was significantly higher in PMF than in ET (45% vs. 34%), and type 1-like and type 2-like mutations were detected in 49% and 51% patients, respectively. Patients with MPN and type 2-like mutation showed a significantly higher median platelet count than those with type 1-like mutation. Particularly, patients with ET and type 2-like mutation had no thrombotic events, despite higher platelet counts. The effect of CALR mutant burden differed depending on the mutant type. A higher mutant burden tended to be associated with a cytopenic phenotype (i.e., lower hemoglobin levels and platelet counts) in patients with the type 1-like mutation and a proliferative hematological phenotype (i.e., higher platelet and neutrophil counts) in patients with the type 2-like mutation. This study suggests that the disease phenotype of MPN may be altered through CALR mutant burden and mutant type.

Correlation analysis of tumor purity with clinicopathological, molecular, and imaging features in high-grade gliomas

High-grade gliomas (HGG) have high malignancy, high heterogeneity, and a poor prognosis. Tumor purity is an intrinsic feature of the HGG microenvironment and an independent prognostic factor. The purpose of this study was to analyze the correlation of tumor purity with clinicopathological, molecular, and imaging features. We performed a retrospective analysis of 112 patients diagnosed with HGG (grades III and IV) in our center. Eleven regions of interest (ROI) were randomly selected on whole-slide images (WSI, 40 × magnification) based on HGG tissue paraffin sections and hematoxylin-eosin (H&E) staining. Of these 11 ROIs, five ROIs were visually estimated by pathologists and six ROIs were automatically analyzed using ImageJ software. Last, the average tumor purity (%) of the 11 ROIs was calculated. Correlation analysis of tumor purity with clinicopathological, molecular, and imaging features was conducted. Of the 112 patients included in the study, the mean tumor purity of HGG was 70.96%. There were differences in tumor purity between WHO grades III and IV; the tumor purity of grade IV patients (67.59%) was lower than that of grade III patients (76.00%) (p < 0.001). There were also differences in tumor purity between IDH1 mutant and wild type, and the tumor purity of IDH1 mutant patients was higher than that of IDH1 wild-type patients (p = 0.006). The average range of peritumoral edema was about 19.18 mm, and the diameter of edema, ADC_mean, and ADC_min were negatively correlated with tumor purity(r =  - 0.236, r =  - 0.306, and r =  - 0.242; p < 0.05). The grade of HGG, IDH1 mutant/wild type, peritumoral edema, and ADC value were correlated with tumor purity. HGG grade, IDH1 mutant/wild type, peritumoral edema, and ADC value can predict tumor purity and indirectly reflect patient prognosis.

KRAS mutation allele frequency threshold alters prognosis in right-sided resected pancreatic cancer

BACKGROUND

Next-generation sequencing (NGS) provides information on genetic mutations and mutant allele frequency in tumor specimens. We investigated the prognostic significance of KRAS mutant allele frequency in patients with right-sided pancreatic ductal adenocarcinoma (PDAC) treated with surgical resection.

METHODS

A retrospective study reviewed patients who underwent surgical resection for PDAC and analyzed tumors with an in-house mutational panel. Microdissected samples were studied using an NGS-based assay to detect over 200 hotspot mutations in 42 genes (Pan42) commonly involved in PDAC.

RESULTS

A total of 144 PDAC right-sided surgical patients with a Pan42 panel were evaluated between 2015 and 2020; 121 patients (84%) harbored a KRAS mutation. Detected mutant allele frequencies were categorized as less than 20% (low mKRAS, n = 92) or greater than or equal to 20% (high mKRAS, n = 29). High mKRAS (KRAS ≥ 20%) patients were noted to have shorter disease-free survival after surgery (11.5 ± 2.1 vs. 19.5 ± 3.5 months, p = 0.03), more advanced tumor stage (p = 0.02), larger tumors (3.6 vs. 2.7 cm, p = 0.001), greater tumor cellularity (26% vs. 18%, p = 0.001), and higher rate of distant recurrence (p = 0.03) than low mKRAS patients.

CONCLUSION

This study demonstrates the importance of KRAS mutant allele frequency on pathological characteristics and prognosis in right-sided PDAC treated with surgery.

Ultra-rapid somatic variant detection via real-time targeted amplicon sequencing

Molecular markers are essential for cancer diagnosis, clinical trial enrollment, and some surgical decision making, motivating ultra-rapid, intraoperative variant detection. Sequencing-based detection is considered the gold standard approach, but typically takes hours to perform due to time-consuming DNA extraction, targeted amplification, and library preparation times. In this work, we present a proof-of-principle approach for sub-1 hour targeted variant detection using real-time DNA sequencers. By modifying existing protocols, optimizing for diagnostic time-to-result, we demonstrate confirmation of a hot-spot mutation from tumor tissue in ~52 minutes. To further reduce time, we explore rapid, targeted Loop-mediated Isothermal Amplification (LAMP) and design a bioinformatics tool-LAMPrey-to process sequenced LAMP product. LAMPrey's concatemer aware alignment algorithm is designed to maximize recovery of diagnostically relevant information leading to a more rapid detection versus standard read alignment approaches. Using LAMPrey, we demonstrate confirmation of a hot-spot mutation (250x support) from tumor tissue in less than 30 minutes.

Molecular dissection of a hyper-aggressive CBFB-MYH11/FLT3-ITD-positive acute myeloid leukemia

Acute Myeloid Leukaemia (AML) is a haematological malignancy showing a hypervariable landscape of clinical outcomes and phenotypic differences, explainable by heterogeneity at the cellular and molecular level. Among the most common genomic alterations, CBFB-MYH11 rearrangement and FLT3-ITD gene mutations, have opposite clinical significance and are unfrequently associated. We present here a Molecular Case Report in which these two events co-exist an ultra-aggressive phenotype resulting in death in 4 days from hospital admittance. Somatic and germline Whole Exome Sequencing analysis was performed to uncover other putative driver mutations, de-novo genomic structural events or germline clusters increasing cancer insurgence. Only three mutations in LTK, BCAS2 and LGAS9 were found, unlikely causative of the exhibited phenotype, prompting to additional investigation of the rare CBFB-MYH11/ FLT3-ITD scenario.

Digital pathology and artificial intelligence in translational medicine and clinical practice

Traditional pathology approaches have played an integral role in the delivery of diagnosis, semi-quantitative or qualitative assessment of protein expression, and classification of disease. Technological advances and the increased focus on precision medicine have recently paved the way for the development of digital pathology-based approaches for quantitative pathologic assessments, namely whole slide imaging and artificial intelligence (AI)-based solutions, allowing us to explore and extract information beyond human visual perception. Within the field of immuno-oncology, the application of such methodologies in drug development and translational research have created invaluable opportunities for deciphering complex pathophysiology and the discovery of novel biomarkers and drug targets. With an increasing number of treatment options available for any given disease, practitioners face the growing challenge of selecting the most appropriate treatment for each patient. The ever-increasing utilization of AI-based approaches substantially expands our understanding of the tumor microenvironment, with digital approaches to patient stratification and selection for diagnostic assays supporting the identification of the optimal treatment regimen based on patient profiles. This review provides an overview of the opportunities and limitations around implementing AI-based methods in biomarker discovery and patient selection and discusses how advances in digital pathology and AI should be considered in the current landscape of translational medicine, touching on challenges this technology may face if adopted in clinical settings. The traditional role of pathologists in delivering accurate diagnoses or assessing biomarkers for companion diagnostics may be enhanced in precision, reproducibility, and scale by AI-powered analysis tools.

Tumor Genotyping and Homologous Recombination Repair Gene Variants in Patients With Epithelial Ovarian Cancer: Is Pathogenic Enough?

Our hypothesis was that the predictive accuracy of pathogenic variants in genes participating in the homologous recombination repair (HRR) system in patients with epithelial ovarian cancer (EOC) could be improved by considering additional next-generation sequencing (NGS) metrics. NGS genotyping was performed in tumor tissue, retrospectively and prospectively collected from patients with EOC, diagnosed from 8/1998 to 10/2016. Variants were considered clonal when variant allele frequencies corresponded to >25%. The primary endpoint was overall survival (OS). This study included 501 patients with EOC, predominantly with high-grade serous (75.2%) and advanced stage tumors (81.7%); median age was 58 years (22-84). Pathogenic and clonal pathogenic variants in HRR and/or TP53 genes were identified in 72.8% and 66.5% tumors, respectively. With a median follow-up of 123.9 months, the presence of either pathogenic or clonal pathogenic HRR-only variants was associated with longer OS compared to HRR/TP53 co-mutation (HR=0.54; 95% CI, 0.34-0.87, Wald's p=0.012 and HR=0.45; 95% CI, 0.27-0.78, Wald's p=0.004, respectively). However, only the presence of clonal HRR-only variants was independently associated with improved OS (HR=0.55; 95% CI, 0.32-0.94, p=0.030). Variant clonality and co-occuring TP53 variants affect the predictive value of HRR pathogenic variants for platinum agents in patients with EOC.

Clinical Trial Registration

[ClinicalTrials.gov], identifier [NCT04716374].

vcfView: An Extensible Data Visualization and Quality Assurance Platform for Integrated Somatic Variant Analysis

Motivation:

Somatic mutations can have critical prognostic and therapeutic implications for cancer patients. Although targeted methods are often used to assay specific cancer driver mutations, high throughput sequencing is frequently applied to discover novel driver mutations and to determine the status of less-frequent driver mutations. The task of recovering somatic mutations from these data is nontrivial as somatic mutations must be distinguished from germline variants, sequencing errors, and other artefacts. Consequently, bioinformatics pipelines for recovery of somatic mutations from high throughput sequencing typically involve a large number of analytical choices in the form of quality filters.

Results:

We present vcfView, an interactive tool designed to support the evaluation of somatic mutation calls from cancer sequencing data. The tool takes as input a single variant call format (VCF) file and enables researchers to explore the impacts of analytical choices on the mutant allele frequency spectrum, on mutational signatures and on annotated somatic variants in genes of interest. It allows variants that have failed variant caller filters to be re-examined to improve sensitivity or guide the design of future experiments. It is extensible, allowing other algorithms to be incorporated easily.

Availability:

The shiny application can be downloaded from GitHub (https://github.com/BrianOSullivanGit/vcfView). All data processing is performed within R to ensure platform independence. The app has been tested on RStudio, version 1.1.456, with base R 3.6.2 and Shiny 1.4.0. A vignette based on a publicly available data set is also available on GitHub.

Mutations in long-lived epithelial stem cells and their clonal progeny in pre-malignant lesions and in oral squamous cell carcinoma

Oral squamous cell carcinomas (OSCCs) are the most common cancers of the oral cavity, but the molecular mechanisms driving OSCC carcinogenesis remain unclear. Our group previously established a murine OSCC model based on a 10-week carcinogen [4-nitroquinoline 1-oxide (4-NQO)] treatment. Here we used K14CreERTAM;Rosa26LacZ mice to perform lineage tracing to delineate the mutational profiles in clonal cell populations resulting from single, long-lived epithelial stem cells, here called LacZ+ stem cell clones (LSCCs). Using laser-capture microdissection, we examined mutational changes in LSCCs immediately after the 10-week 4-NQO treatment and >17 weeks after 4-NQO treatment. We found a 1.8-fold ±0.4 (P = 0.009) increase in single-nucleotide variants and insertions/deletions (indels) in tumor compared with pre-neoplastic LSCCs. The percentages of indels and of loss of heterozygosity events were 1.3-fold±0.3 (P = 0.02) and 2.2-fold±0.7 (P = 0.08) higher in pre-neoplastic compared with tumor LSCCs. Mutations in cell adhesion- and development-associated genes occurred in 83% of the tumor LSCCs. Frequently mutated genes in tumor LSCCs were involved in planar cell polarity (Celsr1, Fat4) or development (Notch1). Chromosomal amplifications in 50% of the tumor LSCCs occurred in epidermal growth factor receptor, phosphoinositide 3-kinase and cell adhesion pathways. All pre-neoplastic and tumor LSCCs were characterized by key smoking-associated changes also observed in human OSCC, C>A and G>T. DeconstructSigs analysis identified smoking and head and neck cancer as the most frequent mutational signatures in pre-neoplastic and tumor LSCCs. Thus, this model recapitulates a smoking-associated mutational profile also observed in humans and illustrates the role of LSCCs in early carcinogenesis and OSCCs.

NGS for (Hemato-) Oncology in Belgium: Evaluation of Laboratory Performance and Feasibility of a National External Quality Assessment Program

Next-generation sequencing (NGS) is being integrated into routine clinical practice in the field of (hemato-) oncology to search for variants with diagnostic, prognostic, or therapeutic value at potentially low allelic frequencies. The complex sequencing workflows used require careful validation and continuous quality control. Participation in external quality assessments (EQA) helps laboratories evaluate their performance and guarantee the validity of tests results with the ultimate goal of ensuring high-quality patient care. Here, we describe three benchmarking trials performed during the period 2017-2018 aiming firstly at establishing the state-of-the-art and secondly setting up a NGS-specific EQA program at the national level in the field of clinical (hemato-) oncology in Belgium. DNA samples derived from cell line mixes and artificially mutated cell lines, designed to carry variants of clinical relevance occurring in solid tumors, hematological malignancies, and BRCA1/BRCA2 genes, were sent to Belgian human genetics, anatomic pathology, and clinical biology laboratories, to be processed following routine practices, together with surveys covering technical aspects of the NGS workflows. Despite the wide variety of platforms and workflows currently applied in routine clinical practice, performance was satisfactory, since participating laboratories identified the targeted variants with success rates ranging between 93.06% and 97.63% depending on the benchmark, and few false negative or repeatability issues were identified. However, variant reporting and interpretation varied, underlining the need for further standardization. Our approach showcases the feasibility of developing and implementing EQA for routine clinical practice in the field of (hemato-) oncology, while highlighting the challenges faced.

Differential U2AF1 mutation sites, burden and co-mutation genes can predict prognosis in patients with myelodysplastic syndrome

To investigate the U2AF1 gene mutation site, mutation load and co-mutations genes in patients with myelodysplastic syndrome (MDS) and their effects on prognosis. Gene mutation detection by next-generation sequence and related clinical data of 234 MDS patients were retrospectively collected and analyzed for the relationship between the clinical characteristics, treatment efficacy and prognosis of U2AF1 gene mutation. Among the 234 MDS patients, the U2AF1 gene mutation rate was 21.7% (51 cases), and the median variant allele frequency was 39.5%. Compared with the wild type, the U2AF1 mutant had a higher incidence of chromosome 8 aberration, and was positively correlated with the occurrence of ASXL1, RUNX1, SETBP1 gene mutation, negatively correlated with SF3B1, NPM1 genes mutation (p < 0.05). The most common mutation site of U2AF1 was S34F (32 cases), while U2AF1 Q157P site mutations had a higher incidence of chromosome 7 abnormalities (p = 0.003). The U2AF1 gene mutation more frequently coincided with signal pathway related gene mutations (p = 0.043) with a trend of shortened overall survival. Among patients with U2AF1 gene mutations, those with ASXL1 mutations were prone to develop into acute myeloid leukemia, those with RUNX1 mutations had an increased risk of relapse, and those with TET2 mutations had higher 1-year survival rate. Compared with the patient group of lower mutation load (VAF ≤ 40%), the group with higher mutation load of U2AF1 (VAF > 40%) had a significantly lower 1-year survival rate (46.1% and 80.5%, p = 0.027). The criteria of U2AF1 VAF > 40% is an independent indicator for poor prognosis of MDS patients. VAF > 40% of U2AF1 is an independent factor of short OS in MDS patients. MDS patients with a mutation in the Q157P site of U2AF1 and a higher U2AF1 mutation load suggests poor prognosis, and co-mutated genes in U2AF1 can affect disease progression and prognosis.

Multi-omics Data Analyses Construct TME and Identify the Immune-Related Prognosis Signatures in Human LUAD

Lung cancer has been the focus of attention for many researchers in recent years for the leading contribution to cancer-related death worldwide, in which lung adenocarcinoma (LUAD) is the most common histological type. However, the potential mechanism behind LUAD initiation and progression remains unclear. Aiming to dissect the tumor microenvironment of LUAD and to discover more informative prognosis signatures, we investigated the immune-related differences in three types of genetic or epigenetic characteristics (expression status, somatic mutation, and DNA methylation) and considered the potential roles that these alterations have in the immune response and both the immune-related metabolic and neural systems by analyzing the multi-omics data from The Cancer Genome Atlas (TCGA) portal. Additionally, a four-step strategy based on lasso regression and Cox regression was used to construct the prognostic prediction model. For the prognostic predictions on the independent test set, the performance of the trained models (average concordance index [C-index] = 0.839) is satisfied, with average 1-year, 3-year, and 5-year areas under the curve (AUCs) equal to 0.796, 0.786, and 0.777. Finally, the overall model was constructed based on all samples, which comprised 27 variables and achieved a high degree of accuracy on the 1-year (AUC = 0.861), 3-year (AUC = 0.850), and 5-year (AUC = 0.916) survival predictions.

Genomic characterization and prognostication applied to a Brazilian cohort of patients with myelofibrosis

Genomic characterization of patients with myeloproliferative neoplasms (MPN) may lead to better diagnostic classification, prognostic assessment, and treatment decisions. These goals are particularly important in myelofibrosis (MF). We performed target Next Generation Sequencing for a panel of 255 genes and Chromosome Microarray Analysis (CMA) in 27 patients with MF. Patients were classified according to genomic findings and we compared the performance of a personalized prognostication system with IPSS, MIPSS70 and MIPSS70 + v2. Twenty-six patients presented mutations: 11.1% had single driver mutations in either JAK2, CALR or MPL; 85.2% had mutations in non-restricted genes (median: 2 per patient). CMA was abnormal in 91.7% of the 24 cases with available data. Copy-Number-Neutral Loss-of-Heterozygosity was the most common finding (66.7%). Del13q was the most frequent copy number variation, and we could define a 2.4 Mb minimally affected region encompassing RB1, SUCLA2 and CLLS2 loci. The largest genomic subgroup consisted of patients with mutations in genes involved with chromatin organization and splicing control (40.7%) and the personalized system showed better concordance and accuracy than the other prognostic systems. Comprehensive genomic characterization reveals the striking genetic complexity of MF and, when combined with clinical data, led, in our cohort, to better prognostication performance.

Genetic hallmarks of recurrent/metastatic adenoid cystic carcinoma

BACKGROUNDAdenoid cystic carcinoma (ACC) is a rare malignancy arising in salivary glands and other sites, characterized by high rates of relapse and distant spread. Recurrent/metastatic (R/M) ACCs are generally incurable, due to a lack of active systemic therapies. To improve outcomes, deeper understanding of genetic alterations and vulnerabilities in R/M tumors is needed.METHODSAn integrated genomic analysis of 1,045 ACCs (177 primary, 868 R/M) was performed to identify alterations associated with advanced and metastatic tumors. Intratumoral genetic heterogeneity, germline mutations, and therapeutic actionability were assessed.RESULTSCompared with primary tumors, R/M tumors were enriched for alterations in key Notch (NOTCH1, 26.3% vs. 8.5%; NOTCH2, 4.6% vs. 2.3%; NOTCH3, 5.7% vs. 2.3%; NOTCH4, 3.6% vs. 0.6%) and chromatin-remodeling (KDM6A, 15.2% vs. 3.4%; KMT2C/MLL3, 14.3% vs. 4.0%; ARID1B, 14.1% vs. 4.0%) genes. TERT promoter mutations (13.1% of R/M cases) were mutually exclusive with both NOTCH1 mutations (q = 3.3 × 10-4) and MYB/MYBL1 fusions (q = 5.6 × 10-3), suggesting discrete, alternative mechanisms of tumorigenesis. This network of alterations defined 4 distinct ACC subgroups: MYB+NOTCH1+, MYB+/other, MYBWTNOTCH1+, and MYBWTTERT+. Despite low mutational load, we identified numerous samples with marked intratumoral genetic heterogeneity, including branching evolution across multiregion sequencing.CONCLUSIONThese observations collectively redefine the molecular underpinnings of ACC progression and identify further targets for precision therapies.FUNDINGAdenoid Cystic Carcinoma Research Foundation, Pershing Square Sohn Cancer Research grant, the PaineWebber Chair, Stand Up 2 Cancer, NIH R01 CA205426, the STARR Cancer Consortium, NCI R35 CA232097, the Frederick Adler Chair, Cycle for Survival, the Jayme Flowers Fund, The Sebastian Nativo Fund, NIH K08 DE024774 and R01 DE027738, and MSKCC through NIH/NCI Cancer Center Support Grant (P30 CA008748).

Increased number of subclones in lung squamous cell carcinoma elicits overexpression of immune related genes

Background

Intratumoral heterogeneity is a cause of drug resistance that leads to treatment failure. We investigated the clinical implication of intratumoral heterogeneity inferred from the number of subclones that constituted a tumor and reasoned the etiology of subclonal expansion using RNA sequencing data.

Methods

Simple nucleotide variation, clinical data, copy number variation, and RNA-sequencing data from 481 The Cancer Genome Atlas-Lung Squamous Cell Carcinoma (TCGA-LUSC) cases were obtained from the Genomic Data Commons data portal. Clonal status was estimated from the allele frequency of the mutated genes using the SciClone package.

Results

The number of subclones that comprised a tumor had a positive correlation with the total mutations in a tumor (σ=0.477, P-value <0.001) and tumor stage (σ=0.111, P-value <0.015). Male LUSC tumors had a higher probability of having more subclones than female tumors (2.28 vs. 1.89, P-value =0.002, Welch Two Sample t-test). On comparing the gene expression in the tumors that were comprised of five subclones with those of a single clone, 291 genes were found to be upregulated and 102 genes were found to be downregulated in the five subclone tumors. The upregulated genes included UGT1A10, SRY, FDCSP, MRLM, and EREG, in order of magnitude of upregulation, and the biologic function of the upregulated genes was strongly enriched for the positive regulation of immune processes and inflammatory responses.

Conclusions

Male LUSC tumors were composed of a greater number of subclones than female tumors. The tumors with large numbers of subclones had overexpressed genes that positively regulated the immune processes and inflammatory responses more than tumors that consisted of a single clone.

"Direct to Drug" screening as a precision medicine tool in multiple myeloma

Seventy-six FDA-approved oncology drugs and emerging therapeutics were evaluated in 25 multiple myeloma (MM) and 15 non-Hodgkin’s lymphoma cell lines and in 113 primary MM samples. Ex vivo drug sensitivities were mined for associations with clinical phenotype, cytogenetic, genetic mutation, and transcriptional profiles. In primary MM samples, proteasome inhibitors, dinaciclib, selinexor, venetoclax, auranofin, and histone deacetylating agents had the broadest cytotoxicity. Of interest, newly diagnosed patient samples were globally less sensitive especially to bromodomain inhibitors, inhibitors of receptor tyrosine kinases or non-receptor kinases, and DNA synthesis inhibitors. Clustering demonstrated six broad groupings of drug sensitivity linked with genomic biomarkers and clinical outcomes. For example, our findings mimic clinical observations of increased venetoclax responsiveness in t(11;14) patients but also identify an increased sensitivity profile in untreated patients, standard genetic risk, low plasma cell S-Phase, and in the absence of Gain(1q) and t(4;14). In contrast, increased ex vivo responsiveness to selinexor was associated with biomarkers of poor prognosis and later relapse patients. This “direct to drug” screening resource, paired with functional genomics, has the potential to successfully direct appropriate individualized therapeutic approaches in MM and to enrich clinical trials for likely responders.

Genome analysis of peeling archival cytology samples detects driver mutations in lung cancer

INTRODUCTIONS

When tumor tissue samples are unavailable to search for actionable driver mutations, archival cytology samples can be useful. We investigate whether archival cytology samples can yield reliable genomic information compared to corresponding formalin-fixed paraffin-embedded (FFPE) tumor samples.

PATIENTS AND METHODS

Pretreatment class V archival cytology samples with adequate tumor cells were selected from 172 lung cancer patients. The genomic profiles of the primary lung tumors have been analyzed through whole-exome regions of 53 genes. We compared the genomic profiles based on the oncogenicity and variant allele frequency (VAF) between the archival cytology and the corresponding primary tumors. We also analyzed the genomic profiles of serial cytological samples during the treatment of EGFR-TKI.

RESULTS

A total of 43 patients were analyzed with the paired samples for DNA mutations and other three patients were analyzed for their fusion genes. A total of 672 mutations were detected. Of those, 106 mutations (15.8%) were shared with both samples. Sixty of seventy-seven (77.9%) shared mutations were oncogenic or likely oncogenic mutations with VAF ≧10%. As high as 90% (9/10) actionable driver mutations and ALK and ROS1 fusion genes were successfully detected from archival cytology samples. Sequential analysis revealed the dynamic changes in EGFR-TKI-resistant mutation (EGFR p.T790M) during the course of treatment.

CONCLUSION

Archival cytology sample with adequate tumor cells can yield genetic information compared to the primary tumors. If tumor tissue samples are unavailable, we can use archival cytology samples to search for actionable driver mutations.

High incidence of FLT3 mutations in follicular thyroid cancer: potential therapeutic target in patients with advanced disease stage

Background:

Conventional treatments for follicular thyroid cancer (FTC) can be ineffective, leading to poor prognosis. The aim of this study was to identify mutations associated with FTC that would serve as novel molecular markers of the disease and its outcome and could potentially identify new therapeutic targets.

Methods:

FLT3 mutations were first detected in a 29-year-old White female diagnosed with metastasized, treatment-refractory FTC. Analyses of FLT3 mutational status through next-generation sequencing of formalin-fixed, paraffin-embedded FTC specimens were subsequently performed in 35 randomly selected patients diagnosed with FTC.

Results:

FLT3 mutations were found in 69% of patients. FLT3 mutation-positive patients were significantly older than those that were FLT3 mutation-negative [median age at diagnosis 54 (36–82) versus 45 (27–58) (p = 0.023)]. Patients over 60 years were 23 times more likely to be FLT3 mutation-positive (p = 0.006). However, the number of FLT3 mutations did not correlate with age (r-Pearson: –0.244, p-value: 0.25). A total of 26 mutations were identified in the FLT3 gene with 2–16 FLT3 mutations in each FLT3 mutation-positive patient (mean: 5.6 mutations/patient). Tyrosine kinase domain (TKD) mutations in the FLT3 gene were detected in 58% of FLT3 mutation-positive patients. All FLT3 mutation-positive patients with a disease stage of pT2N1 or worse harbored at least one mutation in the TKD of FLT3.

Conclusions:

There is a wide spectrum and high frequency of FLT3 mutations in FTC. The precise role of FLT3 mutations in the genesis of FTC, as well as its potential role as a therapeutic target, requires further investigation.

Advances in Genomic Profiling and Risk Stratification in Acute Myeloid Leukemia

OBJECTIVE

To review the current state of molecular and genetic profiling of acute myeloid leukemia (AML) and its implications.

DATA SOURCE

Peer-reviewed journal articles.

CONCLUSION

Significant advances in the understanding of the pathology of acute myeloid leukemia have led to refined risk stratification of patients and application of novel targeted therapies based on genetic profiles. Minimal residual disease testing allows for highly sensitive disease surveillance that can be used to predict relapse and assess treatment response.

IMPLICATIONS FOR NURSING PRACTICE

Accurate prognostication and therapeutic decision-making for patients with acute myeloid leukemia is dependent on molecular profiling. Being knowledgeable of the implications of minimal residual disease testing is critical for patient-centered care.

The evolving role of next generation sequencing in myelodysplastic syndromes

Myelodysplastic syndromes (MDS) are clonal haematological disorders characterized by haematopoietic cell dysplasia, peripheral blood cytopenias, and a predisposition for developing acute myeloid leukaemia (AML). Cytogenetics have historically been important in diagnosis and prognosis in MDS, but the growing accessibility of next generation sequencing (NGS) has led to growing research in the roles of molecular genetic variation on clinical decision-making in these disorders. Multiple genes have been previously studied and found to be associated with specific outcomes or disease types within MDS and knowledge of mutations in these genes provides insight into previously defined MDS subtypes. Knowledge of these mutations also informs development of novel therapies in the treatment of MDS. The precise role of NGS in the diagnosis, prognosis and monitoring of MDS remains unclear but the improvements in NGS technology and accessibility affords clinicians an additional practice tool to provide the best care for patients.

The Role of New Technologies in Myeloproliferative Neoplasms

The hallmark of BCR-ABL1-negative myeloproliferative neoplasms (MPNs) is the presence of a driver mutation in JAK2, CALR, or MPL gene. These genetic alterations represent a key feature, useful for diagnostic, prognostic and therapeutical approaches. Molecular biology tests are now widely available with different specificity and sensitivity. Recently, the allele burden quantification of driver mutations has become a useful tool, both for prognostication and efficacy evaluation of therapies. Moreover, other sub-clonal mutations have been reported in MPN patients, which are associated with poorer prognosis. ASXL1 mutation appears to be the worst amongst them. Both driver and sub-clonal mutations are now taken into consideration in new prognostic scoring systems and may be better investigated using next generation sequence (NGS) technology. In this review we summarize the value of NGS and its contribution in providing a comprehensive picture of mutational landscape to guide treatment decisions. Finally, discussing the role that NGS has in defining the potential risk of disease development, we forecast NGS as the standard molecular biology technique for evaluating these patients.

Isocitrate dehydrogenase 1 and 2 mutations, 2-hydroxyglutarate levels, and response to standard chemotherapy for patients with newly diagnosed acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) cells harboring mutations in isocitrate dehydrogenase 1 (IDH1) and isocitrate dehydrogenase 2 (IDH2) produce the oncometabolite 2-hydroxyglutarate (2HG). This study prospectively evaluated the 2HG levels, IDH1/2 mutational status, and outcomes of patients receiving standard chemotherapy for newly diagnosed AML.

METHODS

Serial samples of serum, urine, and bone marrow aspirates were collected from patients newly diagnosed with AML, and 2HG levels were measured with mass spectrometry. Patients with baseline serum 2HG levels greater than 1000 ng/mL or marrow pellet 2HG levels greater than 1000 ng/2 × 10⁶ cells, which suggested the presence of an IDH1/2 mutation, underwent serial testing. IDH1/2 mutations and estimated variant allele frequencies were identified. AML characteristics were compared with the Wilcoxon test and Fisher's exact test. Disease-free survival and overall survival (OS) were evaluated with log-rank tests and Cox regression.

RESULTS

Two hundred and two patients were treated for AML; 51 harbored IDH1/2 mutations. IDH1/2-mutated patients had significantly higher 2HG levels in serum, urine, bone marrow aspirates, and aspirate cell pellets than wild-type patients. A serum 2HG level greater than 534.5 ng/mL was 98.8% specific for the presence of an IDH1/2 mutation. Patients with IDH1/2-mutated AML treated with 7+3-based induction had a 2-year event-free survival (EFS) rate of 44% and a 2-year OS rate of 57%. There was no difference in complete remission rates, EFS, or OS between IDH1/2-mutated and wild-type patients. Decreased serum 2HG levels on day 14 as a proportion of the baseline were significantly associated with improvements in EFS (P = .047) and OS (P = .019) in a multivariate analysis.

CONCLUSIONS

Among patients with IDH1/2-mutated AML, 2HG levels are highly specific for the mutational status at diagnosis, and they have prognostic relevance in patients receiving standard chemotherapy.

The Progress of Next Generation Sequencing in the Assessment of Myeloid Malignancies

The introduction and advances on next-generation sequencing have led to novel ways to integrate simultaneous assessment of multiple target genes in routine laboratory analysis. Assessment of myeloid neoplasms with targeted next-generation sequencing panels shows evidence to improve diagnosis, assist therapeutic decisions, provide better information about prognosis, and better detection of minimal residual disease. Herein, we provide information for application and utilization of next-generation sequencing studies with a focus on the most important mutations in acute myeloid leukemia, myelodysplastic syndrome, myeloproliferative neoplasms, and other myelodysplastic / myeloproliferative neoplasms in order to integrate them into the daily clinical practice.

BREAST CANCER HISTOPATHOLOGY IMAGE ANALYSIS PIPELINE FOR TUMOR PURITY ESTIMATION

The translation of genomic sequencing technology to the clinic has greatly advanced personalized medicine. However, the presence of normal cells in tumors is a confounding factor in genome sequence analysis. Tumor purity, or the percentage of cancerous cells in whole tissue section, is a correction factor that can be used to improve the clinical utility of genomic sequencing. Currently, tumor purity is estimated visually by expert pathologists; however, it has been shown that there exist vast inter-observer discrepancies in tumor purity scoring. In this paper, we propose a quantitative image analysis pipeline for tumor purity estimation and provide a systematic comparison between pathologists' scores and our image-based tumor purity estimation.