Expert Review of Molecular Diagnostics最新文献

Introduction: Tumor-infiltrating lymphocytes (TILs) have been investigated as prognostic factors in melanoma. Recent advancements in assessing the tumor microenvironment in the setting of more widespread use of immune checkpoint blockade have reignited interest in identifying predictive biomarkers. This review examines the function and significance of TILs in cutaneous melanoma, evaluating their potential as prognostic and predictive markers.

Areas covered: A literature search was conducted on papers covering tumor infiltrating lymphocytes in cutaneous melanoma available online in PubMed and Web of Science from inception to 1 December 2023, supplemented by citation searching. This article encompasses the assessment of TILs, the role of TILs in the immune microenvironment, TILs as a prognostic factor, TILs as a predictive factor for immunotherapy response, and clinical applications of TILs in the treatment of cutaneous melanoma.

Expert opinion: Tumor-infiltrating lymphocytes play a heterogeneous role in cutaneous melanoma. While they have historically been associated with improved survival, their status as independent prognostic or predictive factors remains uncertain. Novel methods of TIL assessment, such as determination of TIL subtypes and molecular signaling, demonstrate potential for predicting therapeutic response. Further, while their clinical utility in risk-stratification in melanoma treatment shows promise, a lack of consensus data hinders standardized application.

Introduction: While Aspergillus spp. remain the predominant cause of invasive mold infections, non-Aspergillus molds, such as the Mucorales or Fusarium spp., account for an increasing proportion of cases. The diagnosis of non-Aspergillus invasive mold infections (NAIMI) is challenging because of the low sensitivity and delay of conventional microbiological tests. Therefore, there is a particular interest to develop molecular tools for their early detection in blood or other clinical samples.

Areas covered: This extensive review of the literature discusses the performance of Mucorales-specific PCR and other genus-specific or broad-range fungal PCR that can be used for the diagnosis of NAIMI in diverse clinical samples, with a focus on novel technologies.

Expert opinion: PCR currently represents the most promising approach, combining good sensitivity/specificity and ability to detect NAIMI in clinical samples before diagnosis by conventional cultures and histopathology. Several PCR assays have been designed for the detection of Mucorales in particular, but also Fusarium spp. or Scedosporium/Lomentospora spp. Some commercial Mucorales PCRs are now available. While efforts are still needed for standardized protocols and the development of more rapid and simpler techniques, PCR is on the way to becoming an essential test for the early diagnosis of mucormycosis and possibly other NAIMIs.

Introduction: Ovarian cancer, characterized by metastasis and reduced 5-year survival rates, stands as a substantial factor in the mortality of gynecological malignancies worldwide. The challenge of delayed diagnosis originates from vague early symptoms and the absence of efficient screening and diagnostic biomarkers for early cancer detection. Recent studies have explored the intricate interplay between ovarian cancer and protein glycosylation, unveiling the potential significance of glycosylation-oriented biomarkers.

Areas covered: This review examines the progress in glycosylation biomarker research, with particular emphasis on advances driven by mass spectrometry-based technologies. We document milestones achieved, discuss encountered limitations, and also highlight potential areas for future research and development of protein glycosylation biomarkers for ovarian cancer.

Expert opinion: The association of glycosylation in ovarian cancer is well known, but current research lacks desired sensitivity and specificity for early detection. Notably, investigations into protein-specific and site-specific glycoproteomics have the potential to significantly enhance our understanding of ovarian cancer and facilitate the identification of glycosylation-based biomarkers. Furthermore, the integration of advanced mass spectrometry techniques with AI-driven analysis and glycome databases holds the promise for revolutionizing biomarker discovery for ovarian cancer, ultimately transforming diagnosis and improving patient outcomes.

Objectives: This study aimed to detect the correlation between SOWAHB polymorphisms and Thyroid cancer (TC) risk in the Chinese Han population.

Methods: We genotyped SOWAHB variants in 510 TC patients and 509 controls using Agena MassARRAY. We assessed the association between SOWAHB polymorphisms and TC susceptibility, with the significant results evaluated through FPRP analysis. We predicted TC risk by the SNP-SNP interaction, analyzed by MDR.

Results: Carriers with rs2703129 CC had a lower probability of TC (codominant, recessive: p = 0.002), while subjects with rs1874564 AG had an increased risk of developing TC (codominant, recessive: p = 0.000, log-additive: p = 0.028). In subjects aged > 45 years, rs2703129 may reduce TC predisposition (codominant: p = 0.011, recessive: p = 0.007), but there was an increased association between rs1874564 and TC risk (codominant: p = 0.030, dominant: p = 0.047). Also, rs2703129 was associated with a lower risk of TC among males (codominant: p = 0.018, recessive: p = 0.013). Conversely, rs1874564 was associated with an increased risk of TC in females (codominant: p = 0.001, dominant: p = 0.003).

Conclusion: SOWAHB SNPs were related to the occurrence of TC, and rs2703129 may be a protective site for TC.

Background: Breathomics is an emerging area focusing on monitoring and diagnosing pulmonary diseases, especially lung cancer. This research aims to employ metabolomic methods to create a breathprint in human-expelled air to rapidly identify lung cancer and its stages.

Research design and methods: An electronic nose (e-nose) system with five metal oxide semiconductor (MOS) gas sensors, a microcontroller, and machine learning algorithms was designed and developed for this application. The volunteers in this study include 114 patients with lung cancer and 147 healthy controls to understand the clinical potential of the e-nose system to detect lung cancer and its stages.

Results: In the training phase, in discriminating lung cancer from controls, the XGBoost classifier model with 10-fold cross-validation gave an accuracy of 91.67%. In the validation phase, the XGBoost classifier model correctly identified 35 out of 42 patients with lung cancer samples and 44 out of 51 healthy control samples providing an overall sensitivity of 83.33% and specificity of 86.27%.

Conclusions: These results indicate that the exhaled breath VOC analysis method may be developed as a new diagnostic tool for lung cancer detection. The advantages of e-nose based diagnostics, such as an easy and painless method of sampling, and low-cost procedures, will make it an excellent diagnostic method in the future.

Introduction: Body fluid markers could be helpful to predict the conversion into clinically definite multiple sclerosis (MS) in people with a first demyelinating event of the central nervous system (CNS). Consequently, biomarkers such as oligoclonal bands, which are integrated in the current MS diagnostic criteria, could assist early MS diagnosis.

Areas covered: This review examines existing knowledge on a broad spectrum of body fluid markers in people with a first CNS demyelinating event, explores their potential to predict conversion to MS, to assess MS disease activity, as well as their utility to differentiate MS from atypical demyelinating disorders such as neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein associated disease.

Expert opinion: This field of research has shown a dramatic increase of evidence, especially in the last decade. Some biomarkers are already established in clinical routine (e.g. oligoclonal bands) while others are currently implemented (e.g. kappa free light chains) or considered as breakthroughs (e.g. neurofilament light). Determination of biomarkers poses challenges for continuous monitoring, especially if exclusively detectable in cerebrospinal fluid. A handful of biomarkers are measurable in blood which holds a significant potential.