Detection of somatic variants and EGFR mutations in cell-free DNA from non-small cell lung cancer patients by ultra-deep sequencing using the ion ampliseq cancer hotspot panel and droplet digital polymerase chain reaction

Targeted metagenomic assessment reflects critical colonization in battlefield injuries

IMPORTANCE

Microbial contamination in combat wounds can lead to opportunistic infections and adverse outcomes. However, current microbiological detection has a limited ability to capture microbial functional genes. This work describes the application of targeted metagenomic sequencing to profile wound bioburden and capture relevant wound-associated signatures for clinical utility. Ultimately, the ability to detect such signatures will help guide clinical decisions regarding wound care and management and aid in the prediction of wound outcomes.

Circulating tumour DNA alterations: emerging biomarker in head and neck squamous cell carcinoma

Head and Neck cancers (HNC) are a heterogeneous group of upper aero-digestive tract cancer and account for 931,922 new cases and 467,125 deaths worldwide. About 90% of these cancers are of squamous cell origin (HNSCC). HNSCC is associated with excessive tobacco and alcohol consumption and infection with oncogenic viruses. Genotyping tumour tissue to guide clinical decision-making is becoming common practice in modern oncology, but in the management of patients with HNSCC, cytopathology or histopathology of tumour tissue remains the mainstream for diagnosis and treatment planning. Due to tumour heterogeneity and the lack of access to tumour due to its anatomical location, alternative methods to evaluate tumour activities are urgently needed. Liquid biopsy approaches can overcome issues such as tumour heterogeneity, which is associated with the analysis of small tissue biopsy. In addition, liquid biopsy offers repeat biopsy sampling, even for patients with tumours with access limitations. Liquid biopsy refers to biomarkers found in body fluids, traditionally blood, that can be sampled to provide clinically valuable information on both the patient and their underlying malignancy. To date, the majority of liquid biopsy research has focused on blood-based biomarkers, such as circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), and circulating microRNA. In this review, we will focus on ctDNA as a biomarker in HNSCC because of its robustness, its presence in many body fluids, adaptability to existing clinical laboratory-based technology platforms, and ease of collection and transportation. We will discuss mechanisms of ctDNA release into circulation, technological advances in the analysis of ctDNA, ctDNA as a biomarker in HNSCC management, and some of the challenges associated with translating ctDNA into clinical and future perspectives. ctDNA provides a minimally invasive method for HNSCC prognosis and disease surveillance and will pave the way in the future for personalized medicine, thereby significantly improving outcomes and reducing healthcare costs.

Liquid biopsy and non-small cell lung cancer: are we looking at the tip of the iceberg?

The possibility to analyse the tumour genetic material shed in the blood is undoubtedly one of the main achievements of translational research in the latest years. In the modern clinical management of advanced non-small cell lung cancer, molecular characterisation plays an essential role. In parallel, immunotherapy is widely employed, but reliable predictive markers are not available yet. Liquid biopsy has the potential to face the two issues and to increase its role in advanced NSCLC in the next future. The aim of this review is to summarise the main clinical applications of liquid biopsy in advanced non-small cell lung cancer, underlining both its potential and limitations from a clinically driven perspective.

HIV-1 Drug Resistance Assay Using Ion Torrent Next Generation Sequencing and On-Instrument End-to-End Analysis Software

HIV-1 antiretroviral therapy management requires sequencing the protease, reverse transcriptase, and integrase portions of the HIV-1 pol gene. Most resistance testing is performed with Sanger sequencing, which has limited ability to detect minor variants. Next generation sequencing (NGS) platforms enable variant detection at frequencies as low as 1% allowing for earlier detection of resistance and modification of therapy. Implementation of NGS assays in the clinical laboratory is hindered by complicated assay design, cumbersome wet bench procedures, and the complexity of data analysis and bioinformatics. We developed a complete NGS protocol and companion analysis and reporting pipeline using AmpliSeq multiplex PCR, Ion Torrent S5 XL sequencing, and Stanford's HIVdb resistance algorithm. Implemented as a Torrent Suite software plugin, the pipeline runs automatically after sequencing. An optimum variant frequency threshold of 10% was determined by comparing Sanger sequences of archived samples from ViroSeq testing, resulting in a sensitivity of 98.2% and specificity of 99.0%. The majority (91%) of drug resistance mutations were detected by both Sanger and NGS, with 1.7% only by Sanger and 7.3% only by NGS. Variant calls were highly reproducible and there was no cross-reactivity to VZV, HBV, CMV, EBV, and HCV. The limit of detection was 500 copies/mL. The NGS assay performance was comparable to ViroSeq Sanger sequencing and has several advantages, including a publicly available end-to-end analysis and reporting plugin. The assay provides a straightforward path for implementation of NGS for HIV drug resistance testing in the laboratory setting without additional investment in bioinformatics infrastructure and resources.

Genetic Characteristics Associated With Drug Resistance in Lung Cancer and Colorectal Cancer Using Whole Exome Sequencing of Cell-Free DNA

Circulating cell-free DNA (cfDNA) can be used to characterize tumor genomes through next-generation sequencing (NGS)-based approaches. We aim to identify novel genetic alterations associated with drug resistance in lung cancer and colorectal cancer patients who were treated with EGFR-targeted therapy and cytotoxic chemotherapy through whole exome sequencing (WES) of cfDNA. A cohort of 18 lung cancer patients was treated with EGFR TKI or cytotoxic chemotherapy, and a cohort of 37 colorectal cancer patients was treated with EGFR monoclonal antibody or cytotoxic chemotherapy alone. Serum samples were drawn before and after development of drug resistance, and the genetic mutational profile was analyzed with WES data. For 110 paired cfDNA and matched germline DNA WES samples, mean coverage of 138x (range, 52–208.4x) and 47x (range, 30.5–125.1x) was achieved, respectively. After excluding synonymous variants, mutants identified in more than two patients at the time of acquired resistance were selected. Seven genes in lung cancer and 16 genes in colorectal cancer were found, namely, APC, TP53, KRAS, SMAD4, and EGFR. In addition, the GPR155 I357S mutation in lung cancer and ADAMTS20 S1597P and TTN R7415H mutations in colorectal cancer were frequently detected at the time of acquired resistance, indicating that these mutations have an important function in acquired resistance to chemotherapy. Our data suggest that novel genetic variants associated with drug resistance can be identified using cfDNA WES. Further validation is necessary, but these candidate genes are promising therapeutic targets for overcoming drug resistance in lung cancer and colorectal cancer.

Cancer Type Classification in Liquid Biopsies Based on Sparse Mutational Profiles Enabled through Data Augmentation and Integration

Identifying the cell of origin of cancer is important to guide treatment decisions. Machine learning approaches have been proposed to classify the cell of origin based on somatic mutation profiles from solid biopsies. However, solid biopsies can cause complications and certain tumors are not accessible. Liquid biopsies are promising alternatives but their somatic mutation profile is sparse and current machine learning models fail to perform in this setting. We propose an improved method to deal with sparsity in liquid biopsy data. Firstly, data augmentation is performed on sparse data to enhance model robustness. Secondly, we employ data integration to merge information from: (i) SNV density; (ii) SNVs in driver genes and (iii) trinucleotide motifs. Our adapted method achieves an average accuracy of 0.88 and 0.65 on data where only 70% and 2% of SNVs are retained, compared to 0.83 and 0.41 with the original model, respectively. The method and results presented here open the way for application of machine learning in the detection of the cell of origin of cancer from liquid biopsy data.

Comparison of the Data of a Next-Generation Sequencing Panel from K-MASTER Project with that of Orthogonal Methods for Detecting Targetable Genetic Alterations

Purpose

K-MASTER project is a Korean national precision medicine platform that screened actionable mutations by analyzing next-generation sequencing (NGS) of solid tumor patients. We compared gene analyses between NGS panel from the K-MASTER project and orthogonal methods.

Materials and Methods

Colorectal, breast, non–small cell lung, and gastric cancer patients were included. We compared NGS results from K-MASTER projects with those of non-NGS orthogonal methods (KRAS, NRAS, and BRAF mutations in colorectal cancer [CRC]; epidermal growth factor receptor [EGFR], anaplastic lymphoma kinase [ALK] fusion, and reactive oxygen species 1 [ROS1] fusion in non–small cell lung cancer [NSCLC], and Erb-B2 receptor tyrosine kinase 2 (ERBB2) positivity in breast and gastric cancers).

Results

In the CRC cohort (n=225), the sensitivity and specificity of NGS were 87.4% and 79.3% (KRAS); 88.9% and 98.9% (NRAS); and 77.8% and 100.0% (BRAF), respectively. In the NSCLC cohort (n=109), the sensitivity and specificity of NGS for EGFR were 86.2% and 97.5%, respectively. The concordance rate for ALK fusion was 100%, but ROS1 fusion was positive in only one of three cases that were positive in orthogonal tests. In the breast cancer cohort (n=260), ERBB2 amplification was detected in 45 by NGS. Compared with orthogonal methods that integrated immunohistochemistry and in situ hybridization, sensitivity and specificity were 53.7% and 99.4%, respectively. In the gastric cancer cohort (n=64), ERBB2 amplification was detected in six by NGS. Compared with orthogonal methods, sensitivity and specificity were 62.5% and 98.2%, respectively.

Conclusion

The results of the K-MASTER NGS panel and orthogonal methods showed a different degree of agreement for each genetic alteration, but generally showed a high agreement rate.

Clinical Implication of Liquid Biopsy in Colorectal Cancer Patients Treated with Metastasectomy

BACKGROUND & AIMS

The application of circulating tumor DNA (ctDNA) has been studied for predicting recurrent disease after surgery and treatment response during systemic treatment. Metastasectomy can be curative for well-selected patients with metastatic colorectal cancer (mCRC). This prospective study investigated the ctDNA level before and after metastasectomy in patients with mCRC to explore its potential as a predictive biomarker.

METHODS

We collected data on 98 metastasectomies for mCRC performed from March 2017 to February 2020. Somatic mutations in the primary and metastatic tumors were identified and tumor-informed ctDNAs were selected by ultra-deep targeted sequencing. Plasma samples were mandatorily collected before and 3-4 weeks after metastasectomy and serially, if patients agreed.

RESULTS

Data on 67 of 98 metastasectomies (58 patients) meeting the criteria were collected. ctDNA was detected in 9 (29%) of 31 cases treated with upfront metastasectomy and in 7 (19.4%) of 36 cases treated with metastasectomy after upfront chemotherapy. The detection rate of ctDNA was higher in liver metastasis (p = 0.0045) and tumors measuring ≥1 cm (p = 0.0183). ctDNA was less likely to be detected if the response to chemotherapy was good. After metastasectomy, ctDNA was found in 4 (6%) cases with rapid progressive disease.

CONCLUSION

The biological factors affecting the ctDNA shedding from the tumor should be considered when applying ctDNA assays in a clinical setting. After metastasectomy for oligometastatic lesions in good responders of chemotherapy, most ctDNA was cleared or existed below the detection level. To assist clinical decision making after metastasectomy for mCRC using ctDNA, further studies for improving specific outcomes are needed.

Copy Number Variation and Rearrangements Assessment in Cancer: Comparison of Droplet Digital PCR with the Current Approaches

The cytogenetic and molecular assessment of deletions, amplifications and rearrangements are key aspects in the diagnosis and therapy of cancer. Not only the initial evaluation and classification of the disease, but also the follow-up of the tumor rely on these laboratory approaches. The therapeutic choice can be guided by the results of the laboratory testing. Genetic deletions and/or amplifications directly affect the susceptibility or the resistance to specific therapies. In an era of personalized medicine, the correct and reliable molecular characterization of the disease, also during the therapeutic path, acquires a pivotal role. Molecular assays like multiplex ligation-dependent probe amplification and droplet digital PCR represent exceptional tools for a sensitive and reliable detection of genetic alterations and deserve a role in molecular oncology. In this manuscript we provide a technical comparison of these two approaches with the golden standard represented by fluorescence in situ hybridization. We also describe some relevant targets currently evaluated with these techniques in solid and hematologic tumors.

Utility of Circulating Tumor DNA in Different Clinical Scenarios of Breast Cancer

Breast cancer is a complex disease whose molecular mechanisms are not completely understood. Developing target therapies is a promising approach. Therefore, understanding the biological behavior of the tumor is a challenge. Tissue biopsy in the metastatic setting remains the standard method for diagnosis. Nevertheless, it has been associated with some disadvantages: It is an invasive procedure, it may not represent tumor heterogeneity, and it does not allow for treatment efficacy to be assessed or early recurrences to be detected. Analysis of circulating tumor DNA (ctDNA) may help to overcome this as it is a non-invasive method of monitoring the disease. In early-stage disease, it can detect early recurrences and monitor tumors' genomic profiles, identifying the emergence of new genetic alterations which can be related to tumor-acquired resistance. In the metastatic setting, the analysis of ctDNA may also allow for the anticipation of clinical and radiological progression of the disease, selection of targeted therapies, and for a photogram of tumor heterogeneity to be provided. It may also detect disease progression earlier in locally advanced tumors submitted to neoadjuvant treatment, and identify minimal residual disease. ctDNA analysis may guide clinical decision-making in different scenarios, in a precision medicine era, once it acts as a repository of genetic tumor material, allowing for a comprehensive mutation profiling analysis. In this review, we focused on recent advances towards the implementation of ctDNA in a clinical routine for breast cancer.

The Clinical Significance of RAS, PIK3CA, and PTEN Mutations in Non-Small Cell Lung Cancer Using Cell-Free DNA

Mutations in the EGFR gene downstream signaling pathways may cause receptor-independent pathway activation, making tumors unresponsive to EGFR inhibitors. However, the clinical significance of RAS, PIK3CA or PTEN mutations in NSCLC is unclear. In this study, patients who were initially diagnosed with NSCLC or experienced recurrence after surgical resection were enrolled, and blood samples was collected. Ultra-deep sequencing analysis of cfDNA using Ion AmpliSeq Cancer Hotspot Panel v2 with Proton platforms was conducted. RAS/PIK3CA/PTEN mutations were frequently detected in cfDNA in stage IV NSCLC (58.1%), and a high proportion of the patients (47.8%) with mutations had bone metastases at diagnosis. The frequency of RAS/PIK3CA/PTEN mutations in patients with activating EGFR mutation was 61.7%. The median PFS for EGFR-TKIs was 15.1 months in patients without RAS/PIK3CA/PTEN mutations, and 19.9 months in patients with mutations (p = 0.549). For patients with activating EGFR mutations, the overall survival was longer in patients without RAS/PIK3CA/PTEN mutations (53.8 months vs. 27.4 months). For the multivariate analysis, RAS/PIK3CA/PTEN mutations were independent predictors of poor prognosis in patients with activating EGFR mutations. In conclusion, RAS, PIK3CA and PTEN mutations do not hamper EGFR-TKI treatment outcome; however, they predict a poor OS when activating EGFR mutations coexist.

The Validity and Predictive Value of Blood-Based Biomarkers in Prediction of Response in the Treatment of Metastatic Non-Small Cell Lung Cancer: A Systematic Review

With the introduction of targeted therapies and immunotherapy, molecular diagnostics gained a more profound role in the management of non-small cell lung cancer (NSCLC). This study aimed to systematically search for studies reporting on the use of liquid biopsies (LB), the correlation between LBs and tissue biopsies, and finally the predictive value in the management of NSCLC. A systematic literature search was performed, including results published after 1 January 2014. Articles studying the predictive value or validity of a LB were included. The search (up to 1 September 2019) retrieved 1704 articles, 1323 articles were excluded after title and abstract screening. Remaining articles were assessed for eligibility by full-text review. After full-text review, 64 articles investigating the predictive value and 78 articles describing the validity were included. The majority of studies investigated the predictive value of LBs in relation to therapies targeting the epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) receptor (n = 38). Of studies describing the validity of a biomarker, 55 articles report on one or more EGFR mutations. Although a variety of blood-based biomarkers are currently under investigation, most studies evaluated the validity of LBs to determine EGFR mutation status and the subsequent targeting of EGFR tyrosine kinase inhibitors based on the mutation status found in LBs of NSCLC patients.

Assessing the Concordance of Genomic Alterations between Circulating-Free DNA and Tumour Tissue in Cancer Patients

Somatic alterations to the genomes of solid tumours, which in some cases represent actionable drivers, provide diagnostic and prognostic insight into these complex diseases. Spatial and longitudinal tracking of somatic genomic alterations (SGAs) in patient tumours has emerged as a new avenue of investigation, not only as a disease monitoring strategy, but also to improve our understanding of heterogeneity and clonal evolution from diagnosis through disease progression. Furthermore, analysis of circulating-free DNA (cfDNA) in the so-called "liquid biopsy" has emerged as a non-invasive method to identify genomic information to inform targeted therapy and may also capture the heterogeneity of the primary and metastatic tumours. Considering the potential of cfDNA analysis as a translational laboratory tool in clinical practice, establishing the extent to which cfDNA represents the SGAs of tumours, particularly actionable driver alterations, becomes a matter of importance, warranting standardisation of methods and practices. Here, we assess the utilisation of cfDNA for molecular profiling of SGAs in tumour tissue across a broad range of solid tumours. Moreover, we examine the underlying factors contributing to discordance of detected SGAs between cfDNA and tumour tissue.

The Role Of Circulating Tumor DNA In Therapeutic Resistance

The application of precision medicine in cancer treatment has partly succeeded in reducing the side effects of unnecessary chemotherapeutics and in improving the survival rate of patients. However, with the long-term use of therapy, the dynamically changing intratumoral and intertumoral heterogeneity eventually gives rise to therapeutic resistance. In recent years, a novel testing technology (termed liquid biopsy) using circulating tumor DNAs (ctDNAs) extracted from peripheral blood samples from patients with cancer has brought about new expectations to the medical community. Using ctDNAs, clinicians can trace the heterogeneity pattern to duly adjust individual therapy and prolong overall survival for patients with cancer. Technological advances in detecting and characterizing ctDNAs (eg, development of next-generation sequencing) have provided clinicians with a valuable tool for genotyping tumors individually and identifying genetic and epigenetic alterations of the entire tumor to capture mutations associated with therapeutic resistance.

Monitoring circulating tumor DNA by analyzing personalized cancer-specific rearrangements to detect recurrence in gastric cancer

Circulating tumor DNA (ctDNA) has emerged as a candidate biomarker for cancer screening. However, studies on the usefulness of ctDNA for postoperative recurrence monitoring are limited. The present study monitored ctDNA in postoperative blood by employing cancer-specific rearrangements. Personalized cancer-specific rearrangements in 25 gastric cancers were analyzed by whole-genome sequencing (WGS) and were employed for ctDNA monitoring with blood up to 12 months after surgery. Personalized cancer-specific rearrangements were identified in 19 samples. The median lead time, which is the median duration between a positive ctDNA detection and recurrence, was 4.05 months. The presence of postoperative ctDNA prior to clinical recurrence was significantly correlated with cancer recurrence within 12 months of surgery (P = 0.029); in contrast, no correlation was found between cancer recurrence and the presence of preoperative ctDNA, suggesting the clinical usefulness of postoperative ctDNA monitoring for cancer recurrence in gastric cancer patients. However, the clinical application of ctDNA can be limited by the presence of ctDNA non-shedders (42.1%, 8/19) and by inconsistent postoperative ctDNA positivity.

Fragments of tumor DNA, or circulating tumor DNA (ctDNA), in blood can help predict stomach cancer recurrence within 12 months of surgery. Kyeong-Man Hong at the National Cancer Center, in Goyang-si, South Korea, and colleagues, carried out whole genome sequencing of stomach tumor samples from 25 patients to identify personalized cancer-specific rearranged DNA sequences. When they used this information to monitor ctDNA in blood samples obtained after surgical removal of the tumor, they found a significant correlation between the presence of ctDNA and cancer recurrence. In most cases, ctDNA was detected around four months prior to clinical recurrence, highlighting the potential usefulness of ctDNA monitoring. The lack of correlation between ctDNA levels and tumor size suggests that further research into the factors determining ctDNA levels is needed.

A novel approach to triple-negative breast cancer molecular classification reveals a luminal immune-positive subgroup with good prognoses

Triple-negative breast cancer is a heterogeneous disease characterized by a lack of hormonal receptors and HER2 overexpression. It is the only breast cancer subgroup that does not benefit from targeted therapies, and its prognosis is poor. Several studies have developed specific molecular classifications for triple-negative breast cancer. However, these molecular subtypes have had little impact in the clinical setting. Gene expression data and clinical information from 494 triple-negative breast tumors were obtained from public databases. First, a probabilistic graphical model approach to associate gene expression profiles was performed. Then, sparse k-means was used to establish a new molecular classification. Results were then verified in a second database including 153 triple-negative breast tumors treated with neoadjuvant chemotherapy. Clinical and gene expression data from 494 triple-negative breast tumors were analyzed. Tumors in the dataset were divided into four subgroups (luminal-androgen receptor expressing, basal, claudin-low and claudin-high), using the cancer stem cell hypothesis as reference. These four subgroups were defined and characterized through hierarchical clustering and probabilistic graphical models and compared with previously defined classifications. In addition, two subgroups related to immune activity were defined. This immune activity showed prognostic value in the whole cohort and in the luminal subgroup. The claudin-high subgroup showed poor response to neoadjuvant chemotherapy. Through a novel analytical approach we proved that there are at least two independent sources of biological information: cellular and immune. Thus, we developed two different and overlapping triple-negative breast cancer classifications and showed that the luminal immune-positive subgroup had better prognoses than the luminal immune-negative. Finally, this work paves the way for using the defined classifications as predictive features in the neoadjuvant scenario.