Search Results (14,460)

Pancreatic cancer (PC) remains one of the malignancies with the most unfavorable prognosis and limited treatment options. The lack of biomarkers for early diagnosis and the asymptomatic nature of the disease contribute to delays in diagnosis and high mortality rates. In recent years, the role of the human microbiota in cancer biology has become increasingly significant, and the oral microbiota in particular has been found to be involved in the pathogenesis and prognosis of several neoplasms. This review summarizes the current evidence relating the salivary microbiota to PC in three key areas: screening and diagnostic potential, pathophysiology and tumor progression, as well as presenting prognostic implications and potential influence on therapy. With regard to early diagnosis, it has been reported that patients with PC have reduced levels of Neisseria elongata (N. elongata) and Streptococcus mitis (S. mitis) and elevated levels of Granulicatella adiacens. Several studies have shown that bacteria present in the saliva can migrate from the oral cavity to pancreatic tissue via hematogenous or enteric routes, where they may actively contribute to tumor development and progression. In particular, it has been shown that Porphyromonas gingivalis (P. gingivalis) and Veillonella atypica (V. atypica) translocate from the mouth to pancreatic tumors, promoting carcinogenesis by inducing a pro-inflammatory tumor microenvironment. Furthermore, some studies have identified certain species associated with prognosis and response to PC treatment. Despite the encouraging results, differences in study methodology, the lack of standardized methods and the scarcity of longitudinal data currently hinder clinical application. Large-scale, multi-omics prospective studies are needed to clarify causality and validate their clinical utility. Overall, the salivary microbiota represents a promising and non-invasive tool for improving early diagnosis, understanding prognosis and enhancing the management of PC. Full article

Oral squamous cell carcinoma (OSCC) frequently develops within chronically injured oral mucosa and may be preceded by clinically recognizable oral potentially malignant disorders (OPMDs), which provide an important window for cancer interception. This review examines how etiological exposures, persistent inflammation, and lesion-specific epithelial–stromal–immune interactions cooperate during the transition from mucosal injury to dysplasia, carcinoma in situ, and invasive OSCC. Major carcinogenic exposures, including tobacco, alcohol, and areca nut, are considered together with context-dependent contributors such as microbial dysbiosis, viral infection, and immune-mediated epithelial injury. At the molecular level, inflammation-driven oral carcinogenesis involves cytokine and chemokine amplification, oxidative and nitrosative stress, NF-κB and STAT3 activation, the COX-2/PGE₂ axis, genomic instability, field cancerization, epithelial–stromal crosstalk, angiogenesis, immune dysregulation, and epigenetic and non-coding RNA-mediated reprogramming. Emerging tools such as molecular risk assessment, liquid biopsy, optical imaging, spatially resolved profiling, and artificial intelligence-assisted models may improve identification of high-risk lesions, although most biomarkers require further prospective validation. Prevention should therefore integrate exposure control, biopsy-based diagnosis, local treatment when indicated, long-term surveillance, and trial-based precision strategies according to lesion risk, intervention window, and safety profile. This review supports a shift from lesion-centered management toward risk-adapted precision prevention in inflammation-driven oral carcinogenesis. Full article

To characterize the distinct expression profiles of microRNAs (miRNAs) in serum and tissue and to delineate the heterogeneity of their regulatory mechanisms in early-stage ovarian cancer (EOC), thereby identifying candidate biomarkers for non-invasive early diagnosis. Differentially expressed miRNAs were identified by integrating publicly available datasets of EOC tissues and serum samples from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Core miRNAs were subsequently screened through integrated differential expression analysis, weighted gene co-expression network analysis (WGCNA), and feature importance ranking derived from optimized machine learning models. Protein–protein interaction (PPI) networks and functional enrichment analyses (GO and KEGG) were performed on predicted target genes to systematically compare the functional discrepancies between serum- and tissue-derived miRNAs. No overlapping core miRNAs were observed between the two compartments. Serum miRNAs exhibited an overall up-regulated trend, whereas tissue miRNAs were predominantly down-regulated. Although the regulatory pathways demonstrated significant heterogeneity, they ultimately converged on the cell cycle and the PI3K-Akt signaling pathway, indicating high functional homology. Furthermore, serum miRNAs are not merely passive leakage products from tissues; current evidence suggests they may be selectively packaged into exosomes to participate in tumor regulation. Despite divergent expression profiles, serum and tissue miRNAs share homologous regulatory functions in EOC. These findings suggest that serum miRNAs accurately reflect the core molecular status of tumor tissues, providing a robust molecular foundation for liquid biopsy-based early detection strategies. Full article

Human papillomavirus (HPV) infection remains the principal etiological factor in cervical cancer development worldwide, with Eastern Europe continuing to demonstrate disproportionately high cervical cancer incidence and mortality rates. Regional disparities in screening implementation, vaccination coverage, and HPV genotype distribution contribute substantially to the persistent burden of HPV-related disease. In recent years, increasing attention has focused on molecular biomarkers and the vaginal microbiome as complementary approaches for improving cervical cancer prevention strategies. This systematic review aimed to evaluate recent evidence regarding HPV genotype distribution, molecular biomarkers, vaginal microbiome composition, and their implications for cervical cancer prevention in Eastern Europe. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, Web of Science, Embase, and the Cochrane Library for studies published between January 2020 and May 2026. This systematic review was conducted in accordance with the PRISMA 2020 guidelines and prospectively registered in PROSPERO (CRD420261391136). Studies from Eastern European populations reporting data on HPV genotype distribution, screening strategies, vaccination, molecular biomarkers, or vaginal microbiome composition were included. HPV prevalence in screening populations ranged from approximately 12% to over 20%, with HPV16 consistently identified as the predominant genotype across all included studies. However, non-16/18 high-risk genotypes, particularly HPV31, HPV51, HPV52, HPV66, and HPV68, represented a substantial proportion of infections in several Eastern European cohorts. Studies evaluating CINtec PLUS cytology and HPV E6/E7 mRNA testing demonstrated improved specificity for identifying clinically significant cervical lesions compared with HPV DNA testing alone. Emerging evidence also suggested associations between vaginal dysbiosis, increased microbial diversity, persistent high-risk HPV infection, and progression to cervical intraepithelial neoplasia. Although the 9-valent HPV vaccine provides coverage for most circulating high-risk genotypes identified in the region, vaccination uptake remains inconsistent throughout Eastern Europe. The findings of this systematic review support the growing importance of extended HPV genotyping, molecular biomarkers, and microbiome-related approaches in cervical cancer prevention strategies in Eastern Europe. Strengthening organized screening programs, expanding vaccination coverage, and improving access to molecular diagnostic technologies remain essential priorities for reducing the regional burden of HPV-related disease. Full article

Prostate cancer remains a major therapeutic challenge, particularly after progression to castration-resistant disease, where persistent androgen receptor signaling, metabolic adaptation, immune escape, and treatment resistance jointly limit clinical benefit. Regulated cell death (RCD) is increasingly recognized not only as an endpoint of tumor cell elimination but also as a dynamic regulator of prostate cancer progression, therapeutic vulnerability, and tumor–immune interactions. In this review, we propose an immunometabolic framework in which androgen receptor signaling, lipid and redox metabolic reprogramming, oxidative stress, and therapeutic pressure converge to shape the susceptibility of prostate cancer cells to distinct RCD modalities. We focus on autophagy and ferroptosis as two extensively studied and translationally relevant pathways, while also discussing emerging roles of necroptosis, pyroptosis, and cuproptosis. Particular attention is given to how RCD-associated signals, including damage-associated molecular patterns, inflammatory mediators, and lipid peroxidation products, may remodel the tumor immune microenvironment and influence the transition between immune-cold and immune-inflamed phenotypes. We further summarize RCD-targeted therapeutic strategies, including ferroptosis induction, autophagy inhibition, nanodrug delivery systems, rational combination therapy, and biomarker-guided patient stratification. Finally, we discuss key translational barriers, including context-dependent biological effects, limited clinical validation, tumor heterogeneity, adaptive resistance, and insufficient predictive biomarkers. By integrating cell death biology with metabolic reprogramming, immune remodeling, and therapeutic resistance, this review highlights RCD as a promising but context-dependent therapeutic vulnerability in advanced prostate cancer. Full article

Lung cancer remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis, biological heterogeneity, and persistent challenges in staging and treatment selection. This narrative review summarizes current and emerging applications of AI across lung cancer screening and early detection, imaging-based staging and prognostication, tissue and liquid biopsy-based tumor characterization, treatment planning, surgical and intraoperative guidance, and drug discovery. In imaging, deep learning models have demonstrated high performance in pulmonary nodule detection, risk stratification, and prediction of molecular alterations, while also showing promise in improving screening efficiency and reducing interpretive variability. In pathology and liquid biopsy domains, AI enables prediction of driver mutations, immunotherapy response, and survival outcomes directly from histopathology slides, circulating tumor DNA, and other blood-based biomarkers, facilitating minimally invasive precision oncology approaches. In treatment planning and delivery, AI systems are being developed to support clinical decision-making, surgical planning (through advanced image segmentation and delineation of operative anatomy), and intraoperative navigation through robotic and computer vision-enabled platforms. Despite these advances, significant barriers remain, including limited real-world validation, algorithmic biases, workflow integration issues, and unresolved ethical and legal concerns. Future progress will depend on the development of transparent, clinically validated, and generalizable AI systems that augment rather than replace the expertise of clinical providers and healthcare teams. Active engagement from pulmonologists, oncologists, radiologists, and thoracic surgeons will be essential in guiding safe implementation and ensuring that AI-driven innovations translate into meaningful improvements in patient outcomes. Full article

Background/Objectives: HER2 overexpression and/or amplification defines a molecularly distinct subset of endometrial carcinomas (ECs) that may benefit from HER2-targeted therapies. However, HER2 testing algorithms remain non-standardized and vary across institutions. This study is a large single-institution audit of EC HER2 testing practices, using both gynecologic (ISGyP) and gastric cancer-specific scoring algorithms at a major academic center with a reference gynecologic oncology service and biomarker laboratory. Methods: HER2 immunohistochemistry (IHC) and whole-slide fluorescence in situ hybridization (FISH) were interpreted by subspecialty breast and gynecologic pathologists, with HER2 IHC performed on 494 tumor samples (2021–2025) and reflex FISH for equivocal cases. Results: Using ISGyP criteria, 15.0% (74/494) of tumors were HER2 IHC 3+, 44.5% (220/494) equivocal (2+), and 40.5% (200/494) were negative (0/1+). Among equivocal cases, 28.2% (58/205) demonstrated ERBB2 amplification, yielding an overall HER2-positive rate of 27.5% (132/480). Re-assessment with gastric scoring criteria demonstrated variability in HER2 classification, with high concordance in cytology specimens (100%) and resections (90.8%; K = 0.842, p < 0.001) but substantially lower concordance in biopsies (60.6%; K = 0.401, p < 0.001), mainly due to reclassification of equivocal cases. Notably, 47.9% (n = 34) of ISGyP-equivocal biopsy specimens were reclassified as HER2 IHC 3+ using gastric biopsy criteria, potentially expanding eligibility for T-DXd therapy. Conclusions: These findings highlight the evolving nature of HER2 testing in EC and demonstrate the significant impact of scoring methodology on HER2 interpretation. Our results support the development of EC-specific HER2 testing guidelines and a dual-reporting approach incorporating both ISGyP and gastric scoring criteria, with selective confirmatory FISH testing, to optimize patient selection for HER2-targeted therapies. Full article

Immunotherapy has transformed cancer treatment; however, clinical benefit remains limited to a subset of patients, underscoring the need for robust biomarkers that capture tumor-immune interactions across cancer types. In this study, we performed a comprehensive pan-cancer, multi-omics characterization of the immune checkpoint–related molecules CD70, CD80, and TIGIT to evaluate their diagnostic, prognostic, and immunological relevance. Using integrative analyses of transcriptomic, epigenomic, genomic, pharmacogenomic, and single-cell RNA-sequencing data from The Cancer Genome Atlas and complementary resources, we assessed expression patterns, DNA methylation, somatic mutations, copy number alterations, immune infiltration, tumor stemness, and drug sensitivity. CD70, CD80, and TIGIT were broadly dysregulated across multiple malignancies, with coordinated overexpression particularly evident in kidney renal clear-cell carcinoma. Elevated expression of these immune checkpoints was associated with advanced tumor stage, aggressive molecular subtypes, and unfavorable survival outcomes in selected cancers, including uveal melanoma and renal malignancies. Functional analyses revealed significant associations between checkpoint expression and key oncogenic pathways, including epithelial–mesenchymal transition, apoptosis, and hormone receptor signaling, suggesting links with tumor progression and immune activation states. Immune deconvolution analyses indicated that TIGIT expression is associated with a T-cell–inflamed microenvironment and reduced neutrophil infiltration, while CD80 exhibited methylation-dependent associations with immune cell composition. Genomic and epigenetic alterations were found to correlate with checkpoint expression patterns and immune phenotypes across tumor types. Pharmacogenomic profiling identified associations between checkpoint expression and sensitivity to multiple anticancer agents; however, these findings are based on cell line datasets and should be considered predictive. Single-cell transcriptomic analyses further resolved cell-type–specific expression patterns, distinguishing tumor-intrinsic from immune-restricted expression profiles. Collectively, our findings establish CD70, CD80, and TIGIT as integrative biomarkers of tumor progression, immune contexture, and therapeutic response, providing a rationale for their clinical exploitation in precision immuno-oncology. Full article

Background/Objectives: Cervical cancer is mainly driven by persistent infection with high-risk human papillomaviruses (HPV), particularly HPV16 and HPV18. Despite advances in cytology, HPV-DNA testing and vaccination, challenges remain in the triage of HPV-positive individuals, prognostic stratification and prediction of treatment response. Non-coding RNAs (ncRNAs), including microRNAs, long non-coding RNAs and circular RNAs, together with host genetic factors influencing ncRNA expression and emerging lncRNA-encoded peptides, are increasingly recognized as regulators of HPV-associated carcinogenesis. This review summarizes their biological and potential clinical relevance. Methods: A structured literature search was conducted in PubMed and Scopus. Eligible studies included experimental, clinical, observational, genomic and translational investigations on ncRNA dysregulation, circulating or exosomal ncRNAs, treatment-response signatures, host genetic variation and lncRNA-encoded peptides in HPV-associated cervical precancer and cancer. Results: HPV oncoproteins can reshape host ncRNA networks through transcriptional and epigenetic mechanisms. Several miRNAs, lncRNAs and circRNAs are involved in cell-cycle control, apoptosis, senescence, epithelial–mesenchymal transition, immune regulation, DNA repair and treatment resistance. Circulating, exosomal and urinary ncRNA signatures have shown diagnostic or prognostic potential in exploratory cohorts. Specific lncRNAs, including ENSG00000267838/lnc-LENG9-5 and lncRNA-EME1, have been associated with chemoradiotherapy response and radioresistance. The lncRNA-encoded peptide TUBORF represents a novel preclinical therapeutic candidate, while genetic variation may further modulate lncRNA function in HPV-related cervical cancer. Conclusions: ncRNAs are promising candidates for risk stratification, non-invasive diagnosis, treatment-response prediction and therapeutic development in HPV-associated cervical disease. However, evidence remains exploratory, requiring prospective multicentre validation and standardized workflows before clinical implementation. Full article

Background: Microsatellite instability (MSI) and mismatch repair (MMR) deficiency are key predictive biomarkers for immune checkpoint inhibitors (ICIs) in metastatic colorectal cancer (mCRC). In real-world practice, however, diagnostic pathways often involve heterogeneous testing modalities, which may lead to discordant or inconclusive results. Methods: We conducted a retrospective study of patients with mCRC who underwent at least one MSI/MMR assessment between 2015 and 2025. Diagnostic modalities included IHC, tissue-based and liquid-based MSI testing. A predefined decision algorithm classified results as conclusive or inconclusive; discordant cases underwent adjudication that integrated a pathology review, molecular features, and technical considerations. Patients were ultimately assigned to definitive MSS or definitive MSI groups. Clinical characteristics, treatment patterns, and outcomes—particularly in relation to immunotherapy—were evaluated. Results: Among 727 evaluable patients, the MSI/MMR status was conclusive in 695 (95.6%) and inconclusive in 32 (4.4%). Inconclusive cases resulted from isolated MMR protein loss, heterogeneous or equivocal staining, inter-tumoral discordance, or discrepancies between tissue- and liquid-based assays. After adjudication, 54 patients (7.4%) were classified as definitive MSI and 673 (92.6%) as definitive MSS. Definitive MSI tumors were associated with female sex, right-sided primaries, high-grade histology, nodal involvement, and BRAF V600E mutations. Among the definitive MSI patients, 31 (57.4%) received immunotherapy, achieving a complete response rate of 48.4% and an overall response rate of 71.0%. Median PFS and OS were not reached in the definitive MSI group, whereas definitive MSS patients treated with ICIs experienced significantly poorer outcomes. Conclusive and adjudicated MSI groups demonstrated comparable responses to immunotherapy. Conclusions: In real-world practice, a meaningful proportion (4%) of mCRC patients experience inconclusive MSI/MMR assessment, with important clinical implications. Both technical and biological factors contribute to diagnostic uncertainty. Integrating orthogonal testing modalities and applying structured adjudication improves classification accuracy and ensures appropriate access to immunotherapy. Full article

Early detection of hepatocellular carcinoma (HCC) is crucial for curative treatment, yet current screening strategies for high-risk liver cirrhosis (LC) patients lack sufficient sensitivity. This study evaluates plasma cell-free DNA(cfDNA) concentration and fragmentomics as biomarkers to improve HCC diagnosis and prognosis. Plasma samples from 39 HCC and 46 LC patients were analyzed for cfDNA concentration and fragment patterns. A multivariate logistic regression model (CMAC), integrating cfDNA concentration, mononucleosome proportion (%MN), alpha-fetoprotein (AFP), and c-reactive protein (CRP), was developed and validated using Leave-One-Out Cross-Validation and bootstrapping. HCC patients exhibited significantly higher cfDNA concentrations (p < 0.0001) and longer fragment lengths (p < 0.05) compared to LC patients. The CMAC model demonstrated superior diagnostic performance (AUROC = 0.946) compared to AFP alone (AUROC = 0.777, p < 0.001). Notably, in early-stage HCC, the CMAC model remained highly accurate (AUROC = 0.941), whereas AFP failed to reach statistical significance. Higher CMAC scores were significantly associated with advanced BCLC stages (p = 0.009), lymphovascular invasion (p = 0.0063) and reduced overall survival (p = 0.0037). Integration of cfDNA analysis with established clinical markers in the CMAC model shows promise as a complementary tool for the early detection of HCC in LC patients. Validation in larger, multicenter cohorts will be necessary to confirm these findings and their clinical applicability. Full article

Background/Objectives: Merkel cell carcinoma (MCC) is a rare but aggressive skin cancer with a 40% recurrence rate. However, reliable biomarkers for early recurrence detection or treatment guidance are lacking, especially for virus-negative tumors. Circulating tumor DNA (ctDNA), a fragment of tumor-derived cell-free DNA in blood, has emerged across multiple cancers as a minimally invasive precision biomarker to detect minimal residual disease (MRD); predict recurrence; and monitor treatment response. This review’s objective was to summarize recent advances in ctDNA as a tool for therapeutic decision-making in MCC, contextualized by findings in other malignancies. Methods: A comprehensive literature review was performed, focusing on studies published between 2016 and 2026 that evaluate ctDNA in MCC and other cancers. Key prospective trials, observational studies, and case reports were identified through PubMed and relevant conference proceedings. Data on ctDNA assay methods (tumor-informed vs. tumor-agnostic), clinical sensitivity, lead time for recurrence detection, and predictive value for therapy response were extracted and synthesized. Results: Across cancers such as colorectal, lung, and melanoma, ctDNA positivity after curative treatment predicts relapse months in advance of imaging and can guide adjuvant therapy decisions. In MCC, recent studies demonstrate that ctDNA levels correlate with MCC tumor burden and exhibit high sensitivity and specificity for clinically evident disease. Stage I-III MCC patients who were ctDNA-positive within four months of treatment had a 7.4-fold higher recurrence risk within the subsequent 12–18 months of follow-up. Serial ctDNA monitoring may enable earlier intervention in otherwise asymptomatic ctDNA-positive MCC cases, helping distinguish responders from non-responders. Conclusions: ctDNA is an emerging precision biomarker that offers significant prognostic and surveillance utility in MCC. It enables earlier detection of recurrence, potentially allowing treatment to begin before clinical disease manifests. It also helps stratify patients by risk and treatment response, informing personalized surveillance intensity and therapeutic choices. Integrating ctDNA monitoring into MCC management could improve outcomes by guiding timely interventions, although prospective trials are needed to confirm that ctDNA-guided decisions translate to improved patient survival. Formal cost-effectiveness analyses have not yet been conducted and represent an important area for future investigation. Full article

Cholangiocarcinoma (CCA) is an aggressive and molecularly heterogeneous malignancy characterized by a profoundly immunosuppressive tumor microenvironment (TME) and historically limited therapeutic options. Recent advances have redefined the treatment paradigm, with phase III trials establishing chemoimmunotherapy as a standard of care and multi-omic profiling elucidating the interplay between tumor genomics, stromal architecture, and immune regulation. Despite these gains, durable clinical benefit remains confined to a minority of patients, reflecting convergent mechanisms of primary and acquired resistance—including immune exclusion, myeloid-dominant suppression, and genotype-driven “cold” tumor states. In this review, we synthesize emerging insights into the immune landscape of CCA, integrating data from single-cell, spatial, and translational studies to define the cellular and molecular circuits governing immune evasion. Beyond canonical biomarkers such as mismatch repair and microsatellite status, we highlight how spatial organization of immunity—in particular, tertiary lymphoid structures, dynamic myeloid and stromal interactions, and pathway-level features—shape immunotherapy responsiveness. We also examine how tumor-intrinsic alterations, including IDH1 mutation, FGFR2 fusions, KRAS activation, and MTAP loss, define distinct immunologic phenotypes with direct implications for immunotherapeutic response and biomarker-driven patient selection. We evaluate the expanding clinical trial landscape of immunotherapy in CCA and more broadly in BTC, including adoptive cell therapies and cancer vaccines. Together, these advances position CCA as a paradigm of how tumor genotype and microenvironment co-evolve to define immunotherapy sensitivity and resistance. Full article

Venous thromboembolism (VTE) significantly impacts lung adenocarcinoma outcomes, yet current predictive tools lack precision. We investigated plasma extracellular vesicle (EV) mRNA as a liquid biopsy source to identify a pro-thrombotic molecular profile in VTE patients. Within a prospective cohort of 260 patients, we performed a retrospective nested case–control study, matching 10 VTE cases with 11 thrombosis-free controls. Plasma EV-RNA was analyzed via high-throughput sequencing. Differentially expressed genes (DEGs) were integrated with functional enrichment and explored across public non-cancer VTE datasets, buffy coat samples, and cell lines. RNA-seq identified 483 DEGs within the VTE patient EV compartment, predominantly linked to neutrophil degranulation (NETosis), inflammation, and coagulation. We identified a set of EV-associated candidate genes (SELP, ELANE, MYL9, DNASE1L3) distinguishing cancer-associated thrombosis from non-malignant VTE, along with transcripts (TFPI, FCGR2A) selectively enriched within the EV compartment relative to circulating blood cells. P-selectin (SELP) was the only significantly increased marker, providing the strongest complementary support at the protein level. This molecular state was detectable prior to the occurrence of VTE. Plasma EVs capture a multicellular mRNA profile, reflecting the systemic immunothrombotic activation in lung adenocarcinoma. Despite sample size limitations, these findings should be considered exploratory and hypothesis-generating, but they suggest the EV-derived mRNA in combination with circulating markers such as SELP may provide a framework for future studies aimed at improving risk stratification. Full article

Human saliva is a heterogeneous bodily fluid with a complex composition, which contains antibodies, proteins, and viruses, making it applicable in clinical diagnosis. There are several advantages of the analysis of saliva samples over other biofluids, including a non-invasive and simple collection procedure for extraoral detection. Biomarker or pathogen detection in saliva can be performed with various methods: mass spectrometry, PCR, ELISA, electrochemical, and optical methods such as fluorescence, SPR, and SERS. The early detection of cancer and other disease biomarkers, as well as infectious agents, can be crucial for effective treatment and minimization of mortality from those diseases. The following paper reviews extraoral detection techniques to identify the most sensitive methods for diagnosing early and asymptomatic patients. The LODs collected and tabulated from 149 analytical papers, alongside the sensitivity, specificity, and sometimes the area under the curve (AUC) tabulated from 118 clinical studies, have all become parameters for the comparative quantitative analysis. Based on the limited but substantial number of analytical studies on the detection of cortisol in saliva (29), the electrochemical platforms demonstrated the highest sensitivity, with a geometric mean LOD of 11 pM. Within these methods, voltametric ones showed the best performance with 6 pM geometric mean LOD. Electrochemical techniques are then followed by immunoassay- and mass spectrometry-based platforms, with corresponding geometric average LOD values of 39.1 and 171 pM, respectively. However, clinical outcomes are at least as meaningful as LOD values. In terms of clinical analysis, ELISA and direct-SERS outperformed other methods, achieving balanced accuracy of approximately 87% and AUC values of 0.96 for direct SERS and 0.86 for ELISA. MS and PCR followed closely, with balanced accuracies around 84%. While the direct SERS is not yet widespread in clinical applications, its potential can be forged if the standardization issue is addressed. Full article