Tumor Biology最新文献

Background: Despite successful response to first line therapy, patients with small-cell lung cancer (SCLC) often suffer from early relapses and disease progression.

Objective: To investigate the relevance of serum tumor markers for estimation of prognosis at several time points during the course of disease.

Methods: In a prospective, single-center study, serial assessments of progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), cytokeratin-19 fragments (CYFRA 21-1) and carcino-embryogenic antigen (CEA) were performed during and after chemotherapy in 232 SCLC patients, and correlated with therapy response and overall survival (OS).

Results: ProGRP, NSE and CYFRA 21-1 levels decreased quickly after the first chemotherapy cycle and correlated well with the radiological response. Either as single markers or in combination they provided valuable prognostic information regarding OS at all timepoints investigated: prior to first-line therapy, after two treatment cycles in patients with successful response to first-line therapy, and prior to the start of second-line therapy. Furthermore, they were useful for continuous monitoring during and after therapy and often indicated progressive disease several months ahead of radiological changes.

Conclusions: The results indicate the great potential of ProGRP, NSE and CYFRA 21-1 for estimating prognosis and monitoring of SCLC patients throughout the course of the disease.

Background: Patients treated with immune checkpoint inhibitors (ICI) are at risk of adverse events (AEs) even though not all patients will benefit. Serum tumor markers (STMs) are known to reflect tumor activity and might therefore be useful to predict response, guide treatment decisions and thereby prevent AEs.

Objective: This study aims to compare a range of prediction methods to predict non-response using multiple sequentially measured STMs.

Methods: Nine prediction models were compared to predict treatment non-response at 6-months (n = 412) using bi-weekly CYFRA, CEA, CA-125, NSE, and SCC measurements determined in the first 6-weeks of therapy. All methods were applied to six different biomarker combinations including two to five STMs. Model performance was assessed based on sensitivity, while model training aimed at 95% specificity to ensure a low false-positive rate.

Results: In the validation cohort, boosting provided the highest sensitivity at a fixed specificity across most STM combinations (12.9% -59.4%). Boosting applied to CYFRA and CEA achieved the highest sensitivity on the validation data while maintaining a specificity >95%.

Conclusions: Non-response in NSCLC patients treated with ICIs can be predicted with a specificity >95% by combining multiple sequentially measured STMs in a prediction model. Clinical use is subject to further external validation.

Background: Tumor necrosis factor-alpha (TNF-α) is among the vital pro-inflammatory cytokines that potentially exerts a significant influence on the immune response, hence potentially regulating the advancement of cervical lesions.

Objective: Our study objective was to examine the relationship between two single nucleotide polymorphisms (SNPs) (rs1799724 and rs1800629) of TNF-α and the risk of cervical cancer in women from Bangladesh.

Methods: We recruited 133 patients with cervical cancer and 126 healthy individuals for this study. Genotyping was performed using real-time PCR SNP genotyping assay. Multivariate logistic regression analysis was used to determine the odds ratio (OR) along with 95% confidence intervals (CI) and p-values.

Results: For rs1799724 (C > T) polymorphism, TT mutant homozygous genotype carried 3.26 times increased risk of developing cervical cancer (OR = 3.26, 95% CI = 1.15-9.28, p = 0.027). Polymorphism of rs1800629 (G > A) was also related to an elevated risk of cervical cancer. Individuals with the AG heterozygous genotype (OR = 2.85, 95% CI = 1.20-6.74, p = 0.017) and AA mutant homozygous genotype (OR = 4.55, 95% CI = 1.24-16.60, p = 0.022) also had a higher likelihood of having cervical cancer. Moreover, we found that injectable contraceptives increase the risk of cervical cancer. Individuals who smoked and/or had first-degree relatives with cancer were more likely to carry the risk allele, which increases the likelihood of developing cervical cancer.

Conclusion: TNF-α polymorphisms in rs1799724 and rs1800629 increase the susceptibility of developing cervical cancer in women from Bangladesh.

Background: Anti-PD-(L)1 immunotherapy has emerged as a promising treatment approach for non-small cell lung cancer (NSCLC), though the response rates remain low. Pre-treatment response prediction may improve patient allocation for immunotherapy. Blood platelets act as active immune-like cells, thereby constraining T-cell activity, propagating cancer metastasis, and adjusting their spliced mRNA content.

Objective: We investigated whether platelet RNA profiles before start of nivolumab anti-PD1 immunotherapy may predict treatment responses.

Methods: We performed RNA-sequencing of platelet RNA samples isolated from stage III-IV NSCLC patients before treatment with nivolumab. Treatment response was scored by the RECIST-criteria. Data were analyzed using a predefined thromboSeq analysis including a particle-swarm-enhanced support vector machine (PSO/SVM) classification algorithm.

Results: We collected and processed a 286-samples cohort, separated into a training/evaluation and validation series and subjected those to training of the PSO/SVM-classification algorithm. We observed only low classification accuracy in the 107-samples validation series (area under the curve (AUC) training series: 0.73 (95% -CI: 0.63-0.84, n = 88 samples), AUC evaluation series: 0.64 (95% -CI: 0.51-0.76, n = 91 samples), AUC validation series: 0.58 (95% -CI: 0.45-0.70, n = 107 samples)), employing a five-RNAs biomarker panel.

Conclusions: We concluded that platelet RNA may have minimally discriminative capacity for anti-PD1 nivolumab response prediction, with which the current methodology is insufficient for diagnostic application.

Background: The value of serum tumor markers (STMs) in the current therapeutic landscape of lung cancer is unclear.

Objective: This scoping review gathered evidence of the predictive, prognostic, and monitoring value of STMs for patients with advanced lung cancer receiving immunotherapy (IT) or targeted therapy (TT).

Methods: Literature searches were conducted (cut-off: May 2022) using PubMed and Cochrane CENTRAL databases. Medical professionals advised on the search strategies.

Results: Study heterogeneity limited the evidence and inferences from the 36 publications reviewed. While increased baseline levels of serum cytokeratin 19 fragment antigen (CYFRA21-1) and carcinoembryonic antigen (CEA) may predict IT response, results for TT were less clear. For monitoring IT-treated patients, STM panels (including CYFRA21-1, CEA, and neuron-specific enolase) may surpass the power of single analyses to predict non-response. CYFRA21-1 measurement could aid in monitoring TT-treated patients, but the value of CEA in this context requires further investigation. Overall, baseline and dynamic changes in individual or combined STM levels have potential utility to predict treatment outcome and for monitoring of patients with advanced lung cancer.

Conclusions: In advanced lung cancer, STMs provide additional relevant clinical information by predicting treatment outcome, but further standardization and validation is warranted.

Background: Programmed cell death receptors and ligands in cancer tissue samples are established companion diagnostics for immune checkpoint inhibitor (ICI) therapies.

Objective: To investigate the relevance of soluble PD-1, PD-L1 and PD-L2 for estimating therapy response and prognosis in non-small cell lung cancer patients (NSCLC) undergoing platin-based combination chemotherapies.

Methods: In a biomarker substudy of a prospective, multicentric clinical trial (CEPAC-TDM) on advanced NSCLC patients, soluble PD-1, PD-L1 and PD-L2 were assessed in serial serum samples by highly sensitive enzyme-linked immunosorbent assays and correlated with radiological response after two cycles of chemotherapy and with overall survival (OS).

Results: Among 243 NSCLC patients, 185 achieved response (partial remission and stable disease) and 58 non-response (progression). The distribution of PD-1, PD-L1 and PD-L2 at baseline (C1), prior to staging (C3) and the relative changes (C3/C1) greatly overlapped between the patient groups with response and non-response, thus hindering the discrimination between the two groups. None of the PD markers had prognostic value regarding OS.

Conclusions: Neither soluble PD-1, PD-L1 nor PD-L2 did provide clinical utility for predicting response to chemotherapy and prognosis. Studies on the relevance of PD markers in ICI therapies are warranted.

 Clinical laboratories are responsible for performing lung cancer tumor marker testing as part of routine clinical care. It is their responsibility to guarantee that the reported tumor marker results are reliable and meet the necessary quality standards for proper clinical use. During the different laboratory phases, pre-analytical, analytical and post-analytical, specific steps and processes can introduce errors and generate incorrect clinical interpretation. This editorial briefly outlines critical laboratory issues related to lung cancer tumor markers, specific for each of these three laboratory phases.

The cumulative pool of cell-free DNA (cfDNA) molecules within bodily fluids represents a highly dense and multidimensional information repository. This "biological mirror" provides real-time insights into the composition, function, and dynamics of the diverse genomes within the body, enabling significant advancements in personalized molecular medicine. However, effective use of this information necessitates meticulous classification of distinct cfDNA subtypes with exceptional precision. While cfDNA molecules originating from different sources exhibit numerous genetic, epigenetic, and physico-chemical variations, they also share common features that complicate analyses. Considerable progress has been achieved in mapping the landscape of cfDNA features, their clinical correlations, and optimizing extraction procedures, analytical approaches, bioinformatics pipelines, and machine learning algorithms. Nevertheless, preanalytical workflows, despite their profound impact on cfDNA measurements, have not progressed at a corresponding pace. In this perspective article, we emphasize the pivotal role of robust preanalytical procedures in the development and clinical integration of cfDNA assays, highlighting persistent obstacles and emerging challenges.

Fundamental studies on biomarkers as well as developed assays for their detection can provide valuable information facilitating clinical decisions. For patients with lung cancer, there are established circulating biomarkers such as serum progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), squamous cell carcinoma antigen (SCC-Ag), carcinoembryonic antigen (CEA), and cytokeratin-19 fragment (CYFRA21-1). There are also molecular biomarkers for targeted therapy such as epidermal growth factor receptor (EGFR) gene, anaplastic lymphoma kinase (ALK) gene, KRAS gene, and BRAF gene. However, there is still an unmet need for biomarkers that can be used for early detection and predict treatment response and survival. In this review, we describe the lung cancer biomarkers that are currently being used in clinical practice. We also discuss emerging preclinical and clinical studies on new biomarkers such as omics-based biomarkers for their potential clinical use to detect, predict, or monitor subtypes of lung cancer. Additionally, between-method differences in tumor markers warrant further development and improvement of the standardization and harmonization for each assay.

Lung cancer (LC) is one of the leading causes for cancer-related deaths in the world, accounting for 28% of all cancer deaths in Europe. Screening for lung cancer can enable earlier detection of LC and reduce lung cancer mortality as was demonstrated in several large image-based screening studies such as the NELSON and the NLST. Based on these studies, screening is recommended in the US and in the UK a targeted lung health check program was initiated. In Europe lung cancer screening (LCS) has not been implemented due to limited data on cost-effectiveness in the different health care systems and questions on for example the selection of high-risk individuals, adherence to screening, management of indeterminate nodules, and risk of overdiagnosis. Liquid biomarkers are considered to have a high potential to address these questions by supporting pre- and post- Low Dose CT (LDCT) risk-assessment thereby improving the overall efficacy of LCS. A wide variety of biomarkers, including cfDNA, miRNA, proteins and inflammatory markers have been studied in the context of LCS. Despite the available data, biomarkers are currently not implemented or evaluated in screening studies or screening programs. As a result, it remains an open question which biomarker will actually improve a LCS program and do this against acceptable costs. In this paper we discuss the current status of different promising biomarkers and the challenges and opportunities of blood-based biomarkers in the context of lung cancer screening.