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Liquid biopsy is a noninvasive diagnostic technique used for monitoring cancer utilizing specific genetic biomarkers present in bodily fluids, such as blood, saliva, or urine. These analyses employ multiple biomolecular sources including circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and exosomes (that contain DNA fragments) to detect genetic biomarkers that can predict, disclose, and/or monitor cancers. Levels of these biomarkers can inform on the presence of cancer, its genetic characteristics, and its potential treatment response and also provide predictive genetic predisposition information for specific cancers including oral squamous cell carcinomas (OSCC). Liquid biopsies can aid cancer management as they offer real-time dynamic information on the response to say chemotherapy or radiotherapy and recurrence following surgical excision. Unlike traditional tissue biopsies, which are invasive with a degree of morbidity and require specific tumor location sampling, liquid biopsies are noninvasive and can be repeated frequently. For oral squamous cell carcinoma, on which this review focuses, liquid biopsy of blood or saliva can be valuable in predicting susceptibility, providing early detection, and monitoring the disease's progression and response to therapy. This review gives a general narrative overview of the technology, its current medical usage, and advantages and disadvantages compared with current techniques and discusses a range of current potential biomarkers for disclosing OSCC and predicting its risk. Oral squamous cell carcinoma is all too often detected in the late stages. In future, liquid biopsy may provide an effective screening process such that cancers including OSCC will be detected in the early stages rather than later when prognosis is poor and morbidity and debilitation are greater. In this screening process, periodontists and hygienists have a critical role in that they are adept in examining mucosa, they see patients with shared risk factors for periodontitis and OSCC, namely smoking and poor oral hygiene, and they see patients frequently such that OSCC examinations should be a routine part of the recall visit. With this additional screening manpower, oral medicine and oral surgery colleagues will detect OSCC earlier and this coupled with new techniques such as liquid biopsy may greatly decrease global morbidity in OSCC., (© 2024 The Authors. Periodontology 2000 published by John Wiley & Sons Ltd.)

Objectives: Non-Hodgkin's lymphoma (NHL) risk assessment is crucial in Sjögren's syndrome (SS). We studied the prevalence of clonal immunoglobulin gene rearrangements in minor salivary glands (MSG) and their correlations with lymphoma occurrence and with previously established NHL predictors., Methods: Molecular B-cell expansion was studied in fresh-frozen MSG of 207 patients with either suspected SS or with suspected lymphoma during SS, using a standardised multiplex PCR assay combined with heteroduplex analysis by microcapillary electrophoresis. The assignation of clonal cases was based on EuroClonality consortium guidelines., Results: Among 207 studied patients, 31 (15%) had MSG monoclonal B-cell infiltration. Monoclonality was significantly more frequent in patients with SS (28/123, 22.8%) compared with patients without SS (3/84, 3.6%, P<0.001). Monoclonal B-cell infiltration in MSG of SS patients correlated significantly with ongoing salivary gland NHL, salivary gland swelling, CD4 + T-cell lymphopenia, rheumatoid factor (RF) activity, low complement levels and type 2 mixed cryoglobulinemia. The accumulation of biological risk factors was associated with a higher rate of MSG B-cell monoclonality given that patients with only positive RF had no probability of MSG B-cell monoclonality, RF-positive patients with 1 or 2 other risk factors had a 25.0% and 85.7% probability of MSG B-cell monoclonality, respectively., Conclusion: The detection of MSG monoclonal B-cell expansion by this easy-to-perform molecular assay is useful, both at the time of diagnosis and during the course of SS. Monoclonal B-cell expansion is associated with a subset of SS patients presenting either ongoing lymphoma or other established lymphoma predictive factors., (Copyright © 2023 Société française de rhumatologie. Published by Elsevier Masson SAS. All rights reserved.)

Introduction: Anti-MAG neuropathies are associated with an IgM monoclonal gammopathy of undetermined significance (MGUS) or with a malignant haemopathy. Our objective was to determine whether the presence of a haemopathy or somatic mutations of MYD88 and CXCR4 genes influences disease presentation and response to rituximab (RTX)., Methods: We included 79 patients (mean age 74 years, disease duration 9.68 years) who had a bone marrow aspiration with morphologic and immunophenotypic analysis. MYD88 L265P and CXCR4 mutations were analysed in peripheral B cells. Information collected included: inflammatory neuropathy cause and treatment sensory sum score (ISS), MRC testing, overall neuropathy limitation scale (ONLS), Rash-built Overall Disability Score (RODS), ataxia score, anti-MAG titres, peak IgM dosage, neurofilament light chain levels, motor and sensory amplitudes, motor unit index (MUNIX) and motor unit size index (MUSIX) sum scores. Efficacy of RTX was evaluated at 12 months in 26 patients., Results: Malignant haematological disorders were discovered in 17 patients (22%): 13 Waldenstrom macroglobulinemia, 3 marginal zone lymphoma and one mantle cell lymphoma. MYD88 L265P mutation was detected in 29/60 (48%) patients and CXCR4 in 1 single patient. Disease severity, biological and electrophysiological data and response to RTX were comparable in patients with MGUS/lymphoma and patients with/without MYD88 L265P mutation. ISS was lower and MUSIX higher in patients improved by RTX., Conclusions: MYD88 L265P mutation and underlying haemopathies are not predictive of a more severe disease. However, in cases of resistant and progressive neuropathy, they provide an opportunity to prescribe newly available drugs such as Bruton tyrosine kinase inhibitors., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.)

Background: Antibiotic resistance is emerging as a global public threat. However, it remains poorly investigated in the context of periodontal therapy. The aim of the study was to investigate the complete diversity of antibiotic resistance genes in a German population., Methods: Thirty-nine volunteers with periodontitis contributed to the present study with one to four periodontal pockets for a total of 124 subgingival samples. Samples were analyzed using shotgun metagenomics., Results: A total of 19 antibiotic resistance genes from six antibiotic classes were detected in subgingival biofilm. Two thirds of the volunteers (n = 26/39) showed antibiotic resistance genes for at least one of the antibiotic classes used for periodontal treatment in dental practice or research: beta-lactam, lincosamide, macrolide, nitroimidazole, and tetracycline. Macrolide was the most abundant class detected (21/39 patients)., Conclusions: Findings from our study suggest a high prevalence of antibiotic resistance genes in periodontal pockets from German volunteers. We recommend the development and broader use of molecular diagnostic tests for antibiotic resistance in dental practice to ensure treatment success and to minimize antibiotic resistance., (© 2023 The Authors. Journal of Periodontology published by Wiley Periodicals LLC on behalf of American Academy of Periodontology.)

The advent of next-generation sequencing (NGS) technologies has revolutionized the field of bioinformatics and genomics, particularly in the area of onco-somatic genetics. NGS has provided a wealth of information about the genetic changes that underlie cancer and has considerably improved our ability to diagnose and treat cancer. However, the large amount of data generated by NGS makes it difficult to interpret the variants. To address this, machine learning algorithms such as Extreme Gradient Boosting (XGBoost) have become increasingly important tools in the analysis of NGS data. In this paper, we present a machine learning tool that uses XGBoost to predict the pathogenicity of a mutation in the myeloid panel. We optimized the performance of XGBoost using metaheuristic algorithms and compared our predictions with the decisions of biologists and other prediction tools. The myeloid panel is a critical component in the diagnosis and treatment of myeloid neoplasms, and the sequencing of this panel allows for the identification of specific genetic mutations, enabling more accurate diagnoses and tailored treatment plans. We used datasets collected from our myeloid panel NGS analysis to train the XGBoost algorithm. It represents a data collection of 15,977 mutations variants composed of a collection of 13,221 Single Nucleotide Variants (SNVs), 73 Multiple Nucleoid Variants (MNVs), and 2683 insertion deletions (INDELs). The optimal XGBoost hyperparameters were found with Differential Evolution (DE), with an accuracy of 99.35%, precision of 98.70%, specificity of 98.71%, and sensitivity of 1.

For decades, the diagnosis, prognosis and thus, the treatment of acute myeloblastic leukemias and myelodysplastic neoplasms has been mainly based on morphological aspects, as evidenced by the French-American-British classification. The morphological aspects correspond quite well, in a certain number of particular cases, to particular evolutionary properties, such as acute myelomonoblastic leukemias with eosinophils or acute promyelocytic leukemias. Advances in biology, particularly "classical" cytogenetics (karyotype) and molecular cytogenetics (in situ hybridization), have made it possible to associate certain morphological features with particular molecular abnormalities, such as the pericentric inversion of chromosome 16 and translocation t(15;17) in the two preceding examples. Polymerase chain reaction techniques have made it possible to go further in these analyses by associating these karyotype abnormalities with their molecular causes, CBFbeta fusion with MYH11 and PML-RAR fusion in the previous cases. In these two examples, the molecular abnormality allows us to better define the pathophysiology of leukemia, to adapt certain treatments (all-transretinoic acid, for example), and to follow up the residual disease of strong prognostic value beyond the simple threshold of less than 5% of marrow blasts, signaling the complete remission. However, the new sequencing techniques of the next generation open up broader perspectives by being able to analyze several dozens of molecular abnormalities, improving all levels of management, from diagnosis to prognosis and treatment, even if it means that morphological aspects are increasingly relegated to the background.

Myeloproliferative neoplasms (MPN) are clonal hematopoietic stem cell-derived disorders characterized by uncontrolled proliferation of differentiated myeloid cells. Two main groups of MPN, BCR::ABL1 -positive (Chronic Myeloid Leukemia) and BCR::ABL1 -negative (Polycythemia Vera, Essential Thrombocytosis, Primary Myelofibrosis) are distinguished. For many years, cytomorphologic and histologic features were the only proof of MPN and attempted to distinguish the different entities of the subgroup BCR::ABL1 -negative MPN. World Health Organization (WHO) classification of myeloid neoplasms evolves over the years and increasingly considers molecular abnormalities to prove the clonal hematopoiesis. In addition to morphological clues, the detection of JAK2, MPL and CALR mutations are considered driver events belonging to the major diagnostic criteria of BCR::ABL1 -negative MPN. This highlights the preponderant place of molecular features in the MPN diagnosis. Moreover, the advent of next-generation sequencing (NGS) allowed the identification of additional somatic mutations involved in clonal hematopoiesis and playing a role in the prognosis of MPN. Nowadays, careful cytomorphology and molecular biology are inseparable and complementary to provide a specific diagnosis and to permit the best follow-up of these diseases.

Background: ALK receptor tyrosine kinase (ALK) aberrations have an established role in pathogenesis of many neoplasms, but their clinical significance in high grade serous ovarian carcinoma (HGSOC) is unclear., Objective: To analyse the frequency of ALK overexpression, molecular abnormalities of ALK, and their impact on the progression-free survival (PFS) and overall survival (OS) in HGSOC., Methods: Protein expression was examined by immunohistochemistry (IHC) using three different clones of anti-ALK antibody. The presence of translocations was analysed using fluorescent in situ hybridization. Next-generation sequencing was used for studying the copy number variation, as well as point mutation and translocations involving other commonly rearranged genes., Results: ALK overexpression was demonstrated in up to 52% of tumours, whereas ALK copy gains in 8.2%, with no clear impact on survival. ALK point mutations were identified in 13 tumours (8.9%), with 3 belonging to the class IV showing significantly better OS. A trend suggesting better PFS was also noticed in these cases. Additionally, three gene fusions were found: ERBB2-GRB7, PRKCA-BRCA1 and SND1-BRAF, none of which has been previously described in HGSOC., Conclusions: HGSOC harbouring activating ALK mutations might be associated with a better survival, while ALK overexpression and ALK amplification does not impact the prognosis.

BCR::ABL1 -negative myeloproliferative neoplasms (MPNs) include three major subgroups-polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF)-which are characterized by aberrant hematopoietic proliferation with an increased risk of leukemic transformation. Besides the driver mutations, which are JAK2, CALR, and MPL , more than twenty additional mutations have been identified through the use of next-generation sequencing (NGS), which can be involved with pathways that regulate epigenetic modifications, RNA splicing, or DNA repair. The aim of this short review is to highlight the impact of molecular biology on the diagnosis, prognosis, and therapeutic management of patients with PV, ET, and PMF.

This study investigated the IgG and IgA antibody response against recombinant S1 and receptor binding domains (RBD) of the spike (S-) protein and the membrane (M-) protein using a set of 115 serum samples collected from patients infected with SARS-CoV-2 in Germany before April 2021 using protein and peptide ELISA. As S1- and RBD-proteins expressed in Escherichia coli provided poor sensitivities in ELISA, they were replaced by proteins expressed in HEK cells. The RBD-ELISA provided a sensitivity of 90.6% (N = 85) for samples collected from patients with confirmed SARS-CoV-2 infections more than 14 days after symptom onset or a positive PCR test. In population-based controls, the specificity was 97.9% (N = 94). In contrast, the sensitivities were only 41.2% and 72.6% for M- and N-proteins, respectively, while the specificities were 88.5% and 100%, respectively. Considering also 20 samples collected during the first two weeks of symptom onset or PCR confirmation, the sensitivity of RBD- and N-protein ELISA decreased to 82.6% and 72.6%, respectively. The combination of two data sets, i.e., N- and RBD-, N- and M-, or RBD- and M-proteins increased the sensitivity to 85.8%, 77.9%, and 87.8%, respectively. Peptide mapping mostly confirmed epitopes previously reported for S1- and M-proteins, but they were only recognized by a few samples already tested positive in the corresponding protein ELISA indicating that peptide-based assays will not improve the diagnostic sensitivity.

There is an ongoing need for high-precision serological assays for the quantitation of anti-SARS-CoV-2 antibodies. Here, a trimeric SARS-CoV-2 spike (S) protein was used to develop an ELISA to quantify specific IgG antibodies present in serum, plasma, and dried blood spots (DBS) collected from infected patients or vaccine recipients. The quantitative S-ELISA was calibrated with international anti-SARS-CoV-2 immunoglobulin standards to provide test results in binding antibody units per mL (BAU/mL). The assay showed excellent linearity, precision, and accuracy. A sensitivity of 100% was shown for samples collected from 54 patients with confirmed SARS-CoV-2 infection more than 14 days after symptom onset or disease confirmation by RT-PCR and 58 vaccine recipients more than 14 days after vaccination. The assay specificity was 98.3%. Furthermore, antibody responses were measured in follow-up samples from vaccine recipients and infected patients. Most mRNA vaccine recipients had a similar response, with antibody generation starting 2-3 weeks after the first vaccination and maintaining positive for at least six months after a second vaccination. For most infected patients, the antibody titers increased during the second week after PCR confirmation. This S-ELISA can be used to quantify the seroprevalence of SARS-CoV-2 in the population exposed to the virus or vaccinated.

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has triggered the worldwide coronavirus disease 2019 (COVID-19) pandemic. Serological assays for the detection of SARS-CoV-2 infections are important to understand the immune response in patients and to obtain epidemiological data about the number of infected people, especially to identify asymptomatic persons not aware of a past infection., Methods: We recombinantly produced SARS-CoV-2 nucleocapsid (N)-protein in Escherichia coli. We used the purified protein to develop an indirect enzyme-linked immunosorbent assay (ELISA) for the detection of SARS-CoV-2 specific antibodies. This ELISA method was optimized and validated with serum samples collected from 113 patients with RT-PCR-confirmed SARS-CoV-2 infections including hospitalized COVID-19 patients and 1500 control sera mostly collected before 2015 with different clinical background., Results: The optimized N-protein-ELISA provided a sensitivity of 89.7% (n = 68) for samples collected from patients with confirmed SARS-CoV-2 infections and mild to severe symptoms more than 14 days after symptom onset or a positive PCR test. The antibody levels remained low for serum samples collected in the first six days (n = 23) and increased in the second week (n = 22) post symptom onset or PCR confirmation. At this early phase, the ELISA provided a sensitivity of 39.1% and 86.4%, respectively, reflecting the time of an IgG immune response against pathogens. The assay specificity was 99.3% (n = 1500; 95% CI 0.995-0.999). Serum samples from persons with confirmed antibody titers against human immunodeficiency viruses 1/2, parvovirus B19, hepatitis A/B virus, cytomegalovirus, Epstein Barr virus, and herpes simplex virus were tested negative., Conclusions: We conclude that the N-protein-based ELISA developed here is well suited for the sensitive and specific serological detection of SARS-CoV-2 specific IgG antibodies in human serum for symptomatic infections. It may also prove useful to identify previous SARS-CoV-2 infections in vaccinated people, as all currently approved vaccines rely on the SARS-CoV-2 spike (S-) protein., (© 2022. The Author(s).)

Most neuronal types have a well-identified electrical phenotype. It is now admitted that a same phenotype can be produced using multiple biophysical solutions defined by ion channel expression levels. This argues that systems-level approaches are necessary to understand electrical phenotype genesis and stability. Midbrain dopaminergic (DA) neurons, although quite heterogeneous, exhibit a characteristic electrical phenotype. However, the quantitative genetic principles underlying this conserved phenotype remain unknown. Here we investigated the quantitative relationships between ion channels' gene expression levels in midbrain DA neurons using single-cell microfluidic qPCR. Using multivariate mutual information analysis to decipher high-dimensional statistical dependences, we unravel co-varying gene modules that link neurotransmitter identity and electrical phenotype. We also identify new segregating gene modules underlying the diversity of this neuronal population. We propose that the newly identified genetic coupling between neurotransmitter identity and ion channels may play a homeostatic role in maintaining the electrophysiological phenotype of midbrain DA neurons.

SAHA (vorinostat) is a histone deacetylase inhibitor approved by the USA Food and Drug Administration (FDA) for treating advanced refractory cutaneous T cell lymphomas. As SAHA alters the expression of many genes under control of the Sp1 transcription factor, we examined the effect of its association with the FDA-approved anticancer antibiotic Mithramycin A (MTR, plicamycin), a competitive inhibitor of Sp1 binding to DNA. Sézary syndrome (SS) cells, expanded ex vivo from peripheral blood mononuclear cells of 4 patients, were tested for their sensitivity to the drugs regarding cytotoxicity and differential responsive gene expression. Multivariate statistical methods were used to identify genes whose expression is altered by SAHA, MTR, and the synergist effect of the two drugs. MTR, like SAHA, induced the apoptosis of SS cells, while the two drugs in combination showed clear synergy or potentiation. Expression data stressed a likely important role of additive or synergistic epigenetic modifications in the combined effect of the two drugs, while direct inhibition of Sp1-dependent transcription seemed to have only limited impact. Ontological analysis of modified gene expression suggested that the two drugs, either independently or synergistically, counteracted many intertwined pro-survival pathways deregulated in SS cells, resistance of these tumors to intrinsic and extrinsic apoptosis, abnormal adhesion migration, and invasive properties, as well as immunosuppressive behavior. Our findings provide preliminary clues on the individual and combined effects of SAHA and MTR in SS cells and highlight a potential therapeutic interest of this novel pair of drugs for treatment of SS patients.