What Does This Mutation Mean? The Tools and Pitfalls of Variant Interpretation in Lymphoid Malignancies

Real life evaluation of AlphaMissense predictions in hematological malignancies

High-throughput sequencing plays a pivotal role in hematological malignancy diagnostics, but interpreting missense mutations remains challenging. In this study, we used the newly available AlphaMissense database to assess the efficacy of machine learning to predict missense mutation effects and its impact to improve our ability to interpret them. Based on the analysis of 2073 variants from 686 patients analyzed for clinical purpose, we confirmed the very high accuracy of AlphaMissense predictions in a large real-life data set of missense mutations (AUC of ROC curve 0.95), and provided a comprehensive analysis of the discrepancies between AlphaMissense predictions and state of the art clinical interpretation.

Next-generation sequencing methodologies to detect low-frequency mutations: "Catch me if you can"

Mutations, the irreversible changes in an organism's DNA sequence, are present in tissues at a variant allele frequency (VAF) ranging from ∼10-8 per bp for a founder mutation to ∼10-3 for a histologically normal tissue sample containing several independent clones - compared to 1%- 50% for a heterozygous tumor mutation or a polymorphism. The rarity of these events poses a challenge for accurate clinical diagnosis and prognosis, toxicology, and discovering new disease etiologies. Standard Next-Generation Sequencing (NGS) technologies report VAFs as low as 0.5% per nt, but reliably observing rarer precursor events requires additional sophistication to measure ultralow-frequency mutations. We detail the challenge; define terms used to characterize the results, which vary between laboratories and sometimes conflict between biologists and bioinformaticists; and describe recent innovations to improve standard NGS methodologies including: single-strand consensus sequence methods such as Safe-SeqS and SiMSen-Seq; tandem-strand consensus sequence methods such as o2n-Seq and SMM-Seq; and ultrasensitive parent-strand consensus sequence methods such as DuplexSeq, PacBio HiFi, SinoDuplex, OPUSeq, EcoSeq, BotSeqS, Hawk-Seq, NanoSeq, SaferSeq, and CODEC. Practical applications are also noted. Several methods quantify VAF down to 10-5 at a nt and mutation frequency (MF) in a target region down to 10-7 per nt. By expanding to > 1 Mb of sites never observed twice, thus forgoing VAF, other methods quantify MF < 10-9 per nt or < 15 errors per haploid genome. Clonal expansion cannot be directly distinguished from independent mutations by sequencing, so it is essential for a paper to report whether its MF counted only different mutations - the minimum independent-mutation frequency MFminI - or all mutations observed including recurrences - the larger maximum independent-mutation frequency MFmaxI which may reflect clonal expansion. Ultrasensitive methods reveal that, without their use, even mutations with VAF 0.5-1% are usually spurious.

Molecular Landscape and Validation of New Genomic Classification in 2668 Adult AML Patients: Real Life Data from the PETHEMA Registry

Next-Generation Sequencing (NGS) implementation to perform accurate diagnosis in acute myeloid leukemia (AML) represents a major challenge for molecular laboratories in terms of specialization, standardization, costs and logistical support. In this context, the PETHEMA cooperative group has established the first nationwide diagnostic network of seven reference laboratories to provide standardized NGS studies for AML patients. Cross-validation (CV) rounds are regularly performed to ensure the quality of NGS studies and to keep updated clinically relevant genes recommended for NGS study. The molecular characterization of 2856 samples (1631 derived from the NGS-AML project; NCT03311815) with standardized NGS of consensus genes (ABL1, ASXL1, BRAF, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, GATA2, HRAS, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NPM1, NRAS, PTPN11, RUNX1, SETBP1, SF3B1, SRSF2, TET2, TP53, U2AF1 and WT1) showed 97% of patients having at least one mutation. The mutational profile was highly variable according to moment of disease, age and sex, and several co-occurring and exclusion relations were detected. Molecular testing based on NGS allowed accurate diagnosis and reliable prognosis stratification of 954 AML patients according to new genomic classification proposed by Tazi et al. Novel molecular subgroups, such as mutated WT1 and mutations in at least two myelodysplasia-related genes, have been associated with an adverse prognosis in our cohort. In this way, the PETHEMA cooperative group efficiently provides an extensive molecular characterization for AML diagnosis and risk stratification, ensuring technical quality and equity in access to NGS studies.

Sequencing of cutaneous squamous cell carcinoma primary tumors and patient-matched metastases reveals ALK as a potential driver in metastases and low mutational concordance in immunocompromised patients

Cutaneous squamous cell carcinoma is a common skin cancer that is responsible for 1,000,000 cases and up to 9,000 deaths annually in the United States. Metastases occur in 2–5% of patients and are responsible for significant morbidity and mortality. The objective of this study is to perform targeted next-generation sequencing on a cohort of squamous cell carcinoma primary tumors and patient-matched lymph node metastases. An oncology 76-gene panel was run from formalin-fixed paraffin-embedded samples of patient-matched primary squamous cell carcinomas (10) and resultant metastases (10). ALK was discovered to be a driver mutation in metastases using two different algorithms, oncoCLUSTand dNdScv. Mutational concordance between primary tumors and metastases was notably lower in immunosuppressed patients, especially among pathogenic mutations (41.7% vs. 83.3%, P = 0.01). Sequencing of matched squamous cell carcinoma primary tumors and lymph node metastases identified genes and pathways that may have clinical importance, most notably ALK as a potential driver mutation of metastasis. Sequencing of both primary tumors and metastases may improve the efficacy of targeted therapies.

The Impact of COVID-19 Pandemic in Portuguese Cancer Patients: A Retrospective Study

Literature reports that SARS-CoV-2 infection in cancer patients may be associated with higher severity and mortality, nevertheless the knowledge is limited. We aimed to describe patients' demographic characteristics and COVID-19 disease outcomes in Portuguese cancer patients. We conducted a retrospective study in a cohort of cancer patients diagnosed with COVID-19. A total of 127 individuals were included: 46.5% males and 53.5% females, with a median age of 72 years. Clinicopathological characteristics were used in univariate and multivariable logistic regression analyses to estimate odds ratios for each variable with outcomes adjusting for potential confounders. Our cohort revealed that 84.3% of patients had more than one risk factor for severe disease rather than cancer. In total, 36.2% of patients were admitted to the Department of Internal Medicine, 14.2% developed severe disease, 1.6% required Intensive Care Unit, and mortality was observed in 11.8%. Severe COVID-19 disease was associated with unfit (ECOG PS > 2) patients (p = 0.009; OR = 6.39; 95% CI: 1.60-25.59), chronic kidney disease (p = 0.004; OR = 20.7; 95% CI: 2.64-162.8), immunosuppression (p < 0.001; OR = 10.3; 95% CI: 2.58-41.2), and presence of respiratory symptoms at diagnosis (p = 0.033; OR = 5.05; 95% CI: 1.14-22.4). Increased risk for mortality was associated with unfit patients (p = 0.036; OR = 4.22; 95% CI: 1.10-16.3), cardiac disease (p = 0.003; OR = 8.26; 95% CI: 2.03-33.6) and immunosuppression (p = 0.022; OR = 5.06; 95% CI: 1.27-20.18). Our results demonstrated that unfit and immunosuppressed patients, with chronic kidney disease and cardiac disease, have, respectively, an increased risk for severe disease and mortality related to COVID-19. Hence, this study provides important information on risk factors for severe COVID-19 disease and associated mortality in a Portuguese cancer population.

Patients with Cancer Appear More Vulnerable to SARS-CoV-2: A Multicenter Study during the COVID-19 Outbreak

The novel COVID-19 outbreak has affected more than 200 countries and territories as of March 2020. Given that patients with cancer are generally more vulnerable to infections, systematic analysis of diverse cohorts of patients with cancer affected by COVID-19 is needed. We performed a multicenter study including 105 patients with cancer and 536 age-matched noncancer patients confirmed with COVID-19. Our results showed COVID-19 patients with cancer had higher risks in all severe outcomes. Patients with hematologic cancer, lung cancer, or with metastatic cancer (stage IV) had the highest frequency of severe events. Patients with nonmetastatic cancer experienced similar frequencies of severe conditions to those observed in patients without cancer. Patients who received surgery had higher risks of having severe events, whereas patients who underwent only radiotherapy did not demonstrate significant differences in severe events when compared with patients without cancer. These findings indicate that patients with cancer appear more vulnerable to SARS-CoV-2 outbreak. SIGNIFICANCE: Because this is the first large cohort study on this topic, our report will provide much-needed information that will benefit patients with cancer globally. As such, we believe it is extremely important that our study be disseminated widely to alert clinicians and patients.This article is highlighted in the In This Issue feature, p. 747.

Functional Characterization of Glucocorticoid Receptor Variants Is Required to Avoid Misinterpretation of NGS Data

Recent advances in genetic analysis technologies such as next-generation sequencing (NGS) have considerably increased the incidental discovery of genetic abnormalities. Six heterozygous missense mutations of the human glucocorticoid receptor (GR; encoded by the NR3C1 gene) have been identified in the context of genetic screening of endocrine pathologies. GR, a nuclear receptor, hormone-induced transcription factor, is involved in many physiological processes. Nevertheless, the pathogenic significance of incidentally discovered mutations remains obscure. The aim of this work was to characterize these variants by evaluating their functional impact on GR signaling. Six original GR variants, located in exon 2, led to amino acid substitutions of the N-terminal domain of GR (F65V, M86V, A229T, A304E, N374S, and R386Q), excluding mainly the activation function tau core 1 domain, the potential site of functional interaction with transcriptional coregulators. Transient cotransfection in HEK293T cells of mutated GR-expressing vectors and a luciferase reporter established dose-response curves for dexamethasone. This excluded any major transactivation abnormality of the mutated GRs (ligand concentration leading to 50% maximal transactivation capacity ≈ 0.2 nM), with maximal transactivation capacity identical to that of the wild-type (WT) GR and without modification of the potentiation of transcriptional coactivator steroid receptor coactivator 2 except in N374S. Moreover, protein expression of mutated GRs and their cytonuclear translocation studied by immunocytochemistry were almost unchanged compared with WT GR. These results underline the silent nature of these missense GR variants and call for cautious interpretation of the discovery of genetic incidentalomas by NGS in the absence of detailed characterization in order to appropriately assess their functional impact on a particular signaling pathway.

The Need for a Consensus Next-generation Sequencing Panel for Mature Lymphoid Malignancies

Supplemental Digital Content is available in the text.

Two-way detection of image features and immunolabeling of lymphoma cells with one-step microarray analysis

Detecting the number of pathological lymphoma cells and lymphocyte subtypes in blood is helpful for clinical diagnosis and typing of lymphoma. In the current study, cell type is identified by cell morphological features and immunolabeled lymphocyte subtypes. Red blood cells and leukocytes were separated using a microfluidic cell chip based on physical blood cell parameters, and leukocytes were identified using five characteristic parameters: energy variance, entropy variance, moment of inertia variance, color mean, and cell area individually. The number of red blood cells that could come into contact with the leukocyte membrane was ≤2 based on the microfluidic injection flow rate of microfluidic chips. Anti-CD3 and anti-CD19 antibodies were used for immunofluorescence staining of T-lymphocyte and B-lymphocyte surface antigens, respectively. The results suggested that the microfluidic assay could detect lymphocyte surface antigen markers and intact leukocytes. Therefore, we report a one-step microfluidic chip for classifying hematological lymphoma cells based on the physical parameters of cells, which can simultaneously measure the overall morphology of blood cells and immunolabeling of lymphocyte surface antigens in one step, solving the current problem of detecting subtypes of hematological lymphoma cells based on multiple methods and multi-step detection.