Background Serum tumor markers such as carcinoembryonic antigen (CEA), alpha-fetoprotein (AFP), and prostate-specific antigen (PSA) are crucial to clinical decision-making based on defined medical thresholds. However, significant inter-method variability and lack of harmonization limit result comparability and hinder consistent application of international guidelines. Objective This letter proposes an expanded role for External Quality Assessment (EQA) programs as active drivers of assay harmonization beyond conventional proficiency testing. Methods This proposal draws on recent studies evaluating the commutability of frozen human serum pools (FSPs) from the Korean Association of External Quality Assessment Service (KEQAS) and findings from EQA-based harmonization simulations. It demonstrated that harmonization of tumor markers such as CA 15-3 and CEA, is achievable. Results KEQAS FSPs demonstrated commutability for AFP, CEA, and total PSA across major diagnostic platforms. Simulation results indicated that “in silico” recalibration substantially reduced inter-method variability; for example, the bias range for CA 15-3 was reduced from [−29.28%, 9.86%] to [−0.09%, 0.12%], and recalibrating outlier methods for CEA improved the alignment also. Conclusions EQA programs can serve as practical harmonization hubs by leveraging commutable materials and implementing EQA-driven recalibration. Such approaches can help that medical decision points, retain consistent clinical significance across diverse analytical systems.
BackgroundTriple-negative breast cancer (TNBC) remains clinically challenging due to its aggressive nature, high recurrence rate, and lack of targeted therapies. To address these limitations, combination chemotherapies that synergistically enhance antitumor efficacy while permitting dose reduction and supporting dose-sparing strategies are urgently needed. Cisplatin has a broad spectrum of anticancer activity. However, its resistance and dose-limiting toxicities constrain clinical benefit. Digitoxin is a cardiac glycoside that has anticancer activity.ObjectiveWe aimed to assess the nature of interaction between digitoxin and cisplatin in TNBC cells, define the most synergistic area (MSA), and estimate dose-sparing potential.MethodsWe profiled digitoxin-cisplatin effects in MDA-MB-231 TNBC cell line by checkerboard and fixed-ratio designs, quantifying interaction with Chou-Talalay combination index/dose-reduction index by CompuSyn, and multiple matrix models by SynergyFinder.ResultsThe CI analysis demonstrated synergy across all tested ratios, with the strongest synergistic interaction at a digitoxin/cisplatin ratio of 1:200 (CI = 0.30 at ED97). Dose-reduction analysis showed up to 27-fold cisplatin sparing (ratio 1:25, ED97). Matrix-based models confirmed synergy (Bliss 6.9, Loewe 18.6, ZIP 7.1, and HSA 14), converging on MSA at 31.25 nM digitoxin and 6.25 µM cisplatin.ConclusionOur results highlight a robust synergistic interaction between digitoxin and cisplatin in MDA-MB-231 cells with a dosing window that maximizes cytotoxic effect while potentially reducing cisplatin exposure.
Background Tumour biomarkers have become increasingly important in oncology, shaping cancer diagnostics, classification, and patient management. Despite their potential, the use of cancer biomarkers in clinical settings remains limited. Objective This paper aims to outline biomarker development, from classical, serum protein markers to emerging tumour biomarkers, including meta-biomarkers, to show their diversity and point out the challenges in their development, reporting, and implementation in clinical practice as well as their relevance in evidence-based pathology and cancer classification. Methods A literature-based analysis, incorporating insights from our ongoing research, is presented. Results Although numerous potential biomarkers, biomarker signatures, and meta-biomarkers, are being discovered, existing innovations are often not supported by sufficiently rigorous research methodologies and standardised reporting practices to enable their translation into clinical practice. Conclusions To ensure that biomarker discoveries are both scientifically sound and clinically useful, improved research and validation methods, along with adherence to established reporting standards, are essential. We propose the use of the Hierarchy of Evidence for Tumour Pathology as a framework to evaluate and map existing evidence and identify knowledge gaps and research priorities.
BackgroundIn recent years, the significance of sirtuins in cancer biology has become increasingly evident, but their molecular mechanisms and prognostic impacts remain elusive.ObjectiveThe present study aimed to investigate the differential expression of the sirtuin gene family across cancers and to evaluate their prognostic value.MethodsWe used various bioinformatics databases and methodologies, including Oncomine, GEPIA, OncoDB, cBioPortal, R2 Kaplan-Meier Scanner, STRING, etc., to determine the expression pattern of the sirtuin family genes, along with their mutations and prognostic values in human cancers.ResultsIn the current study, SIRT1, SIRT2, SIRT4, and SIRT5 were downregulated in lymphoma, whereas SIRT6 and SIRT7 were overexpressed. In breast cancer, SIRT3, SIRT5, and SIRT7 were overexpressed, and in terms of kidney cancer, higher expression of SIRT2, SIRT3, and SIRT5 was observed. In contrast, for leukemia, bladder, and brain cancers, most sirtuin family members showed reduced expression. We found that most mutations occurred in uterine cancer, chRCC (chromophobe renal cell carcinoma), DLBCL (diffuse large B-cell lymphoma), melanoma, pRCC (papillary renal cell carcinoma), and esophageal cancer. Moreover, we identified the relevant functional proteins through protein-protein interaction analysis to evaluate copy number alterations (CNAs) in sirtuins. The most frequent alterations were amplifications and deep deletions. Survival analysis demonstrated that SIRT1 and SIRT2 overexpression correlated with improved overall survival in low-grade glioma but predicted poorer outcomes in ovarian cancer. Downregulation of SIRT1, SIRT3, and SIRT5 was associated with better prognosis in DLBCL, while SIRT3 and SIRT4 upregulation predicted favorable survival in testicular germ cell tumors. SIRT6 overexpression was linked to favorable prognosis in esophageal carcinoma and sarcoma, while unfavorable outcomes were observed in hepatocellular carcinoma and cholangiocarcinoma. SIRT7 upregulation was significantly associated with reduced survival in esophageal, liver, and uterine cancers, but surprisingly correlated with improved outcomes in urothelial carcinoma and cervical squamous cell carcinoma.ConclusionsTogether, this multi-omics analysis reveals the correlation and prognostic values of sirtuins across multiple types of human cancers and suggests that sirtuins may serve as promising biomarkers for different cancers.
Background Osteopontin is a glycophosphoprotein aberrantly expressed in several tumor types, which exhibits several isoforms generated by post-translational and post-transcriptional mechanisms, including alternative splicing. Among total osteopontin (tOPN), the osteopontin-c (OPN-c) splice variant has been the most explored with an oncogenic role described for a range of tumor types. Especially in ovarian cancer (OC) cells, OPN-c is found overexpressed, presenting both diagnostic and prognostic implications. Objective In this review article, we aim to outline OPN-c roles in cancer, particularly in OC, in which it has been reported as a diagnostic biomarker. Methods We used PubMed search, and experimental procedures were summarized at the Figure legends. Results We identified cytoplasmic, perinuclear, and nuclear OPN-c in OC cells that overexpress this OPN splice variant. Moreover, we report that OPN-c splicing isoform is found highly expressed in endometrioid OC patients’ samples, compared to non-neoplastic ovarian tissues. Also, OPN-c expression levels have been associated with worse overall survival and worse progression-free survival in patients with both endometrioid and serous OC. Furthermore, OPN-c may be involved in a wide range of tumor features evoked by signaling pathways, such as AKT, ERK, and FAK. Conclusions Therefore, a better comprehension of OPN-c roles in OC can further contribute to its application as a biomarker as well as a target for putative treatment strategies, especially those aiming to sensitize tumor cells to chemotherapeutic agents currently used in the OC treatment.
Background Migrating strategies of the triple-negative breast cancer (TNBC) together with its role in the establishment of tumor microenvironment (TME), supporting metastasis, have been extensively studied. Extracellular matrix (ECM) is a major player for the TME, establishing the 3D spatial networks with interconnected pores necessary for the mechano-physiological function of the cells. Certain collagen aligners and cross-linkers which are necessary for the formation and the stabilization of ECM networks, however, have not been studied either in normal or in abnormal tissues. Complexities in cell-cell and cell-matrix interactions, and different in types and ratios of ECM proteins in a TME challenge to reveal the precise function of a particular protein that is exhibited by special cells and if specifically present in insignificant amount. Cancer-associated fibroblasts (CAFs) predominantly occupy the major stroma of a solid tumor where they deposit extracellular proteins in the excessive amount compared to other tumor-associated cells. For example, the TNBC tumor itself is positive for asporin (ASPN) since CAFs are major ASPN exhibitors. However, the TNBC cells express it insignificantly. Objective The increase in ECM and its networks suppresses the metastasis. Methods Here, we studied the expression of collagen type I and ASPN in CAFS and MDA-MB-231 (MM231), and evaluated the role of ASPN in collagen alignment and crosslinking. Results TNBC cells have an insignificant expression of ASPN and scanty collagen fibers, some of which aggregate to form the stiff deranged fibers, forming large-size pores in ECM of cancer-cell-dominant outer core of TNBC that support cancer cell invasion and metastasis. Exogenous ASPN and fibroblast-ASPN supported for the collagen alignment and crosslinking that established the small-size pores in the ECM, inhibiting the cancer cell invasion. Conclusions The collagen aligner and the cross-linker, ASPN increases the ECM networks and decreases the migration, and this preliminary study provides the hope that ASPN might be used as an anti-metastatic drug after its confirmation through extensive studies in animal, and positive outcomes through preclinical trials.
Background Immune checkpoint inhibitors (ICIs) provide a significant survival benefit in non-small cell lung cancer (NSCLC) patients; however, accurately predicting which patients will benefit remains a challenge. As previously shown, the STOP model, a machine learning model based on serum tumor markers, is capable of identifying non-responders after 6 weeks of ICIs. Objective This study aims to externally validate this model and to assess the predictive value in combination with radiological response assessment using RECIST criteria. Methods In a cohort of 242 metastatic NSCLC patients, CYFRA, CEA, and NSE were measured before start and after 6 weeks of ICI treatment. The ability of the STOP model to predict no durable benefit (NDB; progressive disease, death within 6 months or disease control of less than 6 months) was assessed using specificity and positive predictive value (PPV). Moreover, a combination of the STOP model with RECIST after 6–8 weeks of ICIs was investigated. Results The STOP model achieved a specificity of 96% (95% CI 95%–97%) and a PPV of predicting NDB of 88.1% (95% CI 85.9%–90.3%). Combining the STOP model with RECIST improved specificity and PPV to 100% and predicted NDB on average 11.6 weeks (IQR 1.8–18.0 weeks) prior to developing radiologically defined progression. Conclusions After 6 weeks of ICIs, the blood-based STOP model was capable of accurately predicting NDB in metastatic NSCLC patients, earlier than conventional radiological assessment. The combined serological and radiological response assessment creates an early opportunity to safely stop ICI treatment in patients who will not benefit, although the clinical utility of the assay is limited since the high specificity comes at the cost of a lower sensitivity.
The optimal positioning and usage of serum tumor markers (STMs) in advanced non-small cell lung cancer (NSCLC) care is still unclear. This review aimed to provide an overview of the potential use and value of STMs in routine advanced NSCLC care for the prediction of prognosis and treatment response. Radiological imaging and clinical symptoms have shown not to capture a patient's entire disease status in daily clinical practice. Since STM measurements allow for a rapid, minimally invasive, and safe evaluation of the patient's tumor status in real time, STMs can be used as companion decision-making support tools before start and during treatment. To overcome the limited sensitivity and specificity associated with the use of STMs, tests should only be applied in specific subgroups of patients and different test characteristics should be defined per clinical context in order to answer different clinical questions. The same approach can similarly be relevant when developing clinical applications for other (circulating) biomarkers. Future research should focus on the approaches described in this review to achieve STM test implementation in advanced NSCLC care.
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: For lung cancer, circulating tumor markers (TM) are available to guide clinical treatment decisions. To ensure adequate accuracy, pre-analytical instabilities need to be known and addressed in the pre-analytical laboratory protocols. OBJECTIVE: This study investigates the pre-analytical stability of CA125, CEA, CYFRA 21.1, HE4 and NSE for the following pre-analytical variables and procedures; i) whole blood stability, ii) serum freeze-thaw cycles, iii) electric vibration mixing and iv) serum storage at different temperatures. METHODS: Left-over patient samples were used and for every investigated variable six patient samples were used and analysed in duplicate. Acceptance criteria were based on analytical performance specifications based on biological variation and significant differences with baseline. RESULTS: Whole blood was stable for at least 6 hours for all TM except for NSE. Two freeze-thaw cycles were acceptable for all TM except CYFRA 21.1. Electric vibration mixing was allowed for all TM except for CYFRA 21.1. Serum stability at 4°C was 7 days for CEA, CA125, CYFRA 21.1 and HE4 and 4 hours for NSE. CONCLUSIONS: Critical pre-analytical processing step conditions were identified that, if not taken into account, will result in reporting of erroneous TM results.
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.
BACKGROUND: It is well established that most colorectal carcinomas arise from conventional adenomas through the adenoma-carcinoma sequence (ACS) model. mitogen-activated protein kinases (MAPKs) pathway has been reported as a crucial player in tumorigenesis. The MAPK signaling pathway is activated by different extracellular signals involving the “mitogen-activated/extracellular signal-regulated kinase 1 (MEK1)”, and this induces the expression of genes involved in proliferation and cellular transformation. Diaphanous-related formin-3 (DIAPH3) acts as a potential metastasis regulator through inhibiting the cellular transition to amoeboid behavior in different cancer types. OBJECTIVE: The aim of the study was to investigate the pattern of immunohistochemical expression of MEK1 and DIAPH3 in colorectal adenoma (CRA) and corresponding colorectal carcinoma (CRC) specimens. METHODS: The immunohistochemical expression of DIAPH3 and MEK1 was examined in 43 cases of CRC and their associated adenomas using tissue microarray technique. RESULTS: MEK1 was overexpressed in 23 CRC cases (53.5%) and in 20 CRA cases (46.5%). DIAPH3 was overexpressed in 11 CRA cases (about 29%) which were significantly lower than CRC (22 cases; 58%) (P = 0.011). Both MEK1 and DIAPH3 overexpression were significantly correlated in CRC (P = 0.009) and CRA cases (P = 0.002). Tumors with MEK1 overexpression had a significantly higher tumor grade (P = 0.050) and perineural invasion (P = 0.017). CONCLUSIONS: Both MEK1 and DIAPH3 are overexpressed across colorectal ACS with strong correlation between them. This co- expression suggests a possible synergistic effect of MEK1 and DIAPH-3 in colorectal ACS. Further large-scale studies are required to investigate the potential functional aspects of MEK1 and DIAPH3 in ACS and their involvement in tumor initiation and the metastatic process.
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: Protein tumor markers are released in high amounts into the blood in advanced non-small cell lung cancer (NSCLC). OBJECTIVE: To investigate the relevance of serum tumor markers (STM) for prognosis, prediction and monitoring of therapy response in NSCLC patients receiving chemotherapy. METHODS: In a biomarker substudy of a prospective, multicentric clinical trial (CEPAC-TDM) on 261 advanced NSCLC patients, CYFRA 21-1, CEA, SCC, NSE, ProGRP, CA125, CA15-3 and HE4 were assessed in serial serum samples and correlated with radiological response after two cycles of chemotherapy and overall (OS) and progression-free survival (PFS). RESULTS: While pretherapeutic STM levels at staging did not discriminate between progressive and non-progressive patients, CYFRA 21-1, CA125, NSE and SCC at time of staging did, and yielded AUCs of 0.75, 0.70, 0.69 and 0.67 in ROC curves, respectively. High pretherapeutic CA15-3 and CA125 as well as high CYFRA 21-1, SCC, CA125 and CA15-3 levels at staging were prognostic for shorter PFS and OS –also when clinical variables were added to the models. CONCLUSIONS: STM at the time of first radiological staging and pretherapeutic CA15-3, CA125 are predictive for first-line treatment response and highly prognostic in patients with advanced NSCLC.
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:Tumor markers (TMs) are a heterogeneous group of molecules used in the diagnosis, prognosis and follow-up of cancer patients. During neoplastic differentiation, cells can either directly synthesize or induce the synthesis of TMs, and the release of these molecules into the bloodstream allows their quantification in biological fluids. Although very small concentrations of TMs are usually present in the serum or plasma of healthy subjects, increased concentrations may also be found in the presence of benign diseases or due to technical interference, producing false positive results.MATERIAL AND METHODS AND RESULTS:Our review analyses the causes of false positives described between January 1970 to February 2023 for the TMs most frequently used in clinical practice: α-fetoprotein (AFP), β2-microglobulin (β2-M), cancer antigen 15-3 (CA 15-3), cancer antigen CA 19-9 (CA 19-9), cancer antigen CA 72-4 (CA 72-4), cancer antigen 125 (CA 125), carcinoembryonic antigen (CEA), chromogranin A (CgA), choriogonadotropin (hCG), cytokeratin 19 fragment (CYFRA 21-1), neuron-specific enolase (NSE), human epididymis protein 4 (HE4), serum HER2 (sHER2), squamous cell carcinoma antigen (SCCA), protein induced by vitamin K absence-II (PIVKA-II), Pro-gastrin-releasing peptide (Pro-GRP), prostate-specific antigen (PSA), Protein S-100 (S-100) and thyroglobulin (Tg). A total of 247 references were included.CONCLUSIONS:A better understanding of pathophysiological processes and other conditions that affect the concentration of TMs might improve the interpretation of results and their clinical application.
Blood-based diagnostics for lung cancer support the diagnosis, estimation of prognosis, prediction, and monitoring of therapy response in lung cancer patients. The clinical utility of serum tumor markers has considerably increased due to developments in serum protein tumor markers analytics and clinical biomarker studies, the exploration of preanalytical and influencing conditions, the interpretation of biomarker combinations and individual biomarker kinetics, as well as the implementation of biostatistical models. In addition, circulating tumor DNA (ctDNA) and other liquid biopsy markers are playing an increasingly prominent role in the molecular tumor characterization and the monitoring of tumor evolution over time. Thus, modern lung cancer biomarkers may considerably contribute to an individualized companion diagnostics and provide a sensitive guidance for patients throughout the course of their disease. In this special edition on Tumor Markers in Lung Cancer, experts summarize recent developments in clinical laboratory diagnostics of lung cancer and give an outlook on future challenges and opportunities.
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.
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.
BACKGROUND: Differential diagnosis of non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) in hospitalized patients is crucial for appropriate treatment choice. OBJECTIVE: To investigate the relevance of serum tumor markers (STMs) and their combinations for the differentiation of NSCLC and SCLC subtypes. METHODS: Between 2000 and 2003, 10 established STMs were assessed retrospectively in 311 patients with NSCLC, 128 with SCLC prior systemic first-line therapy and 51 controls with benign lung diseases (BLD), by automatized electrochemiluminescence immunoassay technology. Receiver operating characteristic (ROC) curves and logistic regression analyses were used to evaluate the diagnostic efficacy of both individual and multiple STMs with corresponding sensitivities at 90% specificity. Standards for Reporting of Diagnostic Accuracy (STARD guidelines) were followed. RESULTS: CYFRA 21-1 (cytokeratin-19 fragment), CEA (carcinoembryonic antigen) and NSE (neuron specific enolase) were significantly higher in all lung cancers vs BLD, reaching AUCs of 0.81 (95% CI 0.76–0.87), 0.78 (0.73–0.84), and 0.88 (0.84–0.93), respectively. By the three marker combination, the discrimination between benign and all malignant cases was improved resulting in an AUC of 0.93 (95% CI 0.90–0.96). In NSCLC vs. BLD, CYFRA 21-1, CEA and NSE were best discriminative STMs, with AUCs of 0.86 (95% CI 0.81–0.91), 0.80 (0.74–0.85), and 0.85 (0.79–0.91). The three marker combination also improved the AUC: 0.92; 95% CI 0.89–0.96). In SCLC vs. BLD, ProGRP (pro-gastrin-releasing peptide) and NSE were best discriminative STMs, with AUCs of 0.89 (95% CI 0.84–0.94) and 0.96 (0.93–0.98), respectively, and slightly improved AUC of 0.97 (95% CI 0.95–0.99) when in combination. Finally, discrimination between SCLC and NSCLC was possible by ProGRP (AUC 0.86; 95% CI 0.81–0.91), NSE (AUC 0.83; 0.78–0.88) and CYFRA 21-1 (AUC 0.69; 0.64–0.75) and by the combination of the 3 STMs (AUC 0.93; 0.91–0.96), with a sensitivity of 88% at 90% specificity. CONCLUSIONS: The results confirm the power of STM combinations for the differential diagnosis of lung cancer from benign lesions and between histological lung cancer subtypes.
