10551 Background: Early identification of cancer remains essential for improving survival and reducing downstream treatment costs, yet effective and scalable multi-cancer screening strategies are still limited. OncoSeek is a previously validated, AI-based multi-cancer early detection (MCED) assay integrating protein tumor markers (PTMs) with clinical data, demonstrating 58.4% sensitivity, 92.0% specificity, and 70.6% tissue-of-origin accuracy in > 15,000 participants. To improve detection of specific cancer types and expand cancer-type coverage, we developed OncoSeek 2.0 by incorporating three additional PTMs and evaluated its performance in validation cohort. Methods: OncoSeek 2.0 retained the original machine-learning framework of OncoSeek 1.0, with expanded PTM inputs (ProGRP, SCCA, and tPSA). Performance was evaluated in a retrospective validation cohort comprising 1,267 cancer and 355 non-cancer individuals. Overall performance, including cancer-type-specific sensitivity, was assessed and compared with OncoSeek 1.0. Results: OncoSeek 2.0 incorporated three additional PTMs (ProGRP, SCCA, and tPSA) to enhance cancer-type–specific detection. ProGRP levels was significantly elevated in small cell lung cancer compared with other cancers and healthy controls; SCCA concentrations were higher in squamous cell carcinomas (esophageal, cervical, and lung) than in non-squamous cancers and controls; and tPSA was selectively increased in prostate cancer (all P < 0.0001). Compared with OncoSeek 1.0, OncoSeek 2.0 achieved a higher AUC (0.917 vs 0.860) and improved sensitivity from 65.3% to 77.6% at 90.1% specificity across 15 pre-specified cancer types collectively accounting for 76.5% of global cancer mortality. Sensitivity gains were notable in lung (75.1% → 84.3%), prostate (58.8% → 88.2%), cervical (55.6% → 65.6%), and esophageal (39.6% → 62.4%) cancers. When stratified by tumor stage, OncoSeek 2.0 achieved sensitivities of 54.2% for stage I, 71.7% for stage II, 79.8% for stage III, and 88.4% for stage IV, consistently outperforming OncoSeek 1.0, which achieved sensitivities of 30.2%, 53.8%, 62.3%, and 85.7% for stages I through IV, respectively. Conclusions: By integrating three additional cancer-type–specific PTMs, OncoSeek 2.0 substantially improves sensitivity while maintaining high specificity and low reagent cost (~$30 per test). The upgraded assay enhances detection across multiple tumor types and disease stages, with particularly pronounced gains in lung, prostate, cervical, and esophageal cancers. These results support OncoSeek 2.0 as a scalable and clinically actionable MCED approach for population-level early detection, particularly for cancers lacking USPSTF-recommended screening and in low- and middle-income countries.

BACKGROUND:Head and neck squamous cell carcinoma (HNSCC) is a common and challenging malignancy, with limited response rates to immune checkpoint inhibitors (ICIs). Accurate blood-based biomarkers are needed to predict immunotherapy responses, aiding patient stratification in neoadjuvant settings. MATERIALS AND METHODS:Baseline peripheral blood samples were collected from 52 newly diagnosed HNSCC patients undergoing neoadjuvant ICI therapy. Immune cell phenotypes were assessed using flow cytometry across three staining panels: Panel A (CD3, CD4, CD8, PD-1, CD28, HLA-DR), Panel B (CD3, CD4, CD8, KLRG-1, CD57), and Panel C (CD3, CD4, CD8, CD45RA, CCR7, CD28, CD38). Retrospective analysis included routine blood counts, biochemical markers, and cytokine levels. The predictive accuracy of individual and combined biomarkers was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS:Six immune markers were elevated in non-responder group (non-R group), including PD-1dim/CD8+ T, PD-1ʰi/CD8+ T, PD-1+/CD8+ T, and CD28-PD-1+/CD8+ T as percentage markers, and HLA-DR+/CD8+ T and HLA-DR+/CD28+PD-1-CD8+ T as mean fluorescence intensity (MFI) markers. Inflammation markers, including WBC, neutrophils (Neut), and CRP, also correlated with response. A combined model of CD28-PD-1+/CD8+ T cells and WBC achieved an area under the curve (AUC) of 0.82 (95% CI: 0.69-0.94), outperforming the Combined Positive Score (CPS; AUC = 0.59, 95% CI: 0.43-0.76). CONCLUSION:These findings suggest that peripheral immune and inflammatory markers, particularly CD28-PD-1+/CD8+ T cells and WBC, can predict ICI response, supporting personalized immunotherapy in HNSCC.

The combination of chemotherapy can enhance the efficacy of immune checkpoint inhibitors (ICIs), but requires precise patient stratification and biomarker screening. Cytokines influence immunotherapy outcomes, and multiplex cytokine profiling aids in identifying predictive biomarkers for ICIs. We analyzed 1331 plasma samples (1025 untreated pan-cancer patients and 306 healthy controls), including 238 receiving ICIs plus chemotherapy. Cytokine clusters were identified via non-negative matrix factorization. Cluster effected on early response and progression-free survival (PFS) were evaluated, and a Cytokine-based ICI Survival Index (CISI) was developed. The effect of specific cytokines on anti-programmed death 1 (PD1) treatment was verified in vivo. Thus, three inflammatory clusters were identified: Cluster 1 (high IFN-γ/IL-8/IL-1β, proinflammatory), Cluster 2 (high IL-6), and Cluster 3 (high IL-5/IL-17, Th2 activation). Cluster 3 showed superior PFS (HR = 2.44/3.84, p = 0.00011) and response rates (85.42 % vs. 54.33 %/61.90 %, p = 0.00075) versus Clusters 1&2. High IFN-γ/IL-8 predicted poorer outcomes. The CISI model, incorporating cytokine clusters and clinical variables (treatment, IL-10, monocyte-to-lymphocyte ratio, and M stage), outperformed conventional biomarkers programmed death-ligand 1 (PD-L1) and IL-8 in predictive efficiency [Concordance indexes (C-indexes) = 0.75 vs. 0.55 and 0.56]. In vivo studies confirmed the effects on anti-PD1 efficacy by characteristic cytokines in clusters. In conclusion, our cytokine clustering based on multi-cytokine profiles and CISI model predicted prognosis and immunotherapeutic response in tumor patients, providing new insights into personalized cancer therapy strategies.

Viral mimicry refers to an active antiviral response triggered by the activation of endogenous retroviruses (ERVs), usually manifested by the formation of double-stranded RNA (dsRNA) and activation of the cellular interferon response, which activates the immune system and produces anti-tumor effects. Epigenetic studies have shown that epigenetic modifications (e.g. DNA methylation, histone modifications, etc.) play a crucial role in tumorigenesis, progression, and treatment resistance. Particularly, alterations in DNA methylation may be closely associated with the suppression of ERVs expression, and treatment by demethylation may restore ERVs activity and thus strengthen the tumor immune response. Therefore, we propose that viral mimicry can induce immune responses in the tumor microenvironment by activating the expression of ERVs, and that epigenetic alterations may play a key regulatory role in this process. In this paper, we review the intersection of viral mimicry, epigenetics and tumor immunotherapy, and explore the possible interactions and synergistic effects among the three, aiming to provide a new theoretical basis and potential strategies for cancer immunotherapy.

Background and objectives:Sex steroid hormones have been hypothesized to be associated with the risk of gastric cancer (GC); however, it has not been widely validated in prospective studies. We aimed to investigate the associations between sex steroid hormone metabolites and the risk of gastric cancer and precancerous lesions in a prospective cohort of Chinese men. Methods:Using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and electrochemical luminescence immunoassay, we examined 20 sex steroid hormone metabolites and sex hormone-binding globulin (SHBG) in serum from 470 eligible men, including high-grade lesions or GC (n = 32), intestinal metaplasia (IM, n = 146), and 1:2 matched normal participants (n = 292) from 2007 to 2012. IM and normal participants were further followed up until December 2021, during which 32 new GC cases were identified with a median follow-up of 11.8 years. Associations between baseline sex steroid hormone metabolites and IM, high-grade lesions and gastric cancer were assessed using logistic regression, and associations between sex steroid hormone metabolites and incident GC risk were assessed using Cox proportional hazards regression in the prospective analysis. Results:In the cross-sectional analysis, androstenedione levels were potentially associated with IM risk and significantly associated with high-grade lesions or GC risk (ORcontinuous = 2.45, 95% CI: 1.01-5.95). Higher concentrations of 17α-hydroxypregnenolone (ORcontinuous = 2.35, 95% CI: 1.13-4.88), progesterone (ORcontinuous = 2.68, 95% CI: 1.09-6.61), and estrone (ORcontinuous = 5.36, 95% CI: 1.28-22.52) were also associated with an increased risk of high-grade lesions or GC. Furthermore, significant positive associations between GC risk and serum levels of SHBG (HRcontinuous = 2.57, 95% CI: 1.04-6.36), epitestosterone (HRcontinuous = 2.10, 95% CI: 1.07-4.15) and pregnenolone (HRcontinuous = 1.30, 95% CI: 1.03-1.63) were identified in the follow-up study focusing on participants diagnosed as normal or IM. Notably, the subgroup analyses stratified by H. pylori status revealed similar associations between androstenedione, 17α-hydroxypregnenolone, progesterone, estrone, SHBG, pregnenolone, and GC risk. Conclusions:Several sex hormone metabolites were significantly associated with gastric cancer and its precancerous lesions, indicating a role for sex hormones in gastric carcinogenesis and potentially providing novel biomarkers for the identification of high-risk populations and risk prediction for GC.

Circulating tumor cells (CTCs) are crucial for understanding tumor heterogeneity and progression. Despite extensive research over the years, most studies have focused on CTCs counting, with fewer efforts directed toward single-cell sequencing (SCS) of CTCs. In this study, we developed two novel nanodevices-a high-porosity ultrathin filter membrane and a nanowell chip- to isolate single CTCs. Automated scanning and single-cell picking systems were employed to locate and isolate individual CTCs, enabling the establishment of an efficient and automated workflow for single CTC sequencing using filter-based systems. We conducted an in-depth comparison to evaluate the effects of different filter membranes and cell adhesion types on genomic integrity, cell viability, sequencing coverage, and depth. The results showed that the high-porosity filter membrane outperformed other photolithographic filters for SCS of CTCs. Validation using NCI-H358 cell lines and patientderived CTCs demonstrated that this workflow could accurately and comprehensively detect gene mutations, amplifications, and copy number variations (CNVs). CNV profiles of CTCs from patients with the same tumor type were highly consistent, while intra-patient CTCs revealed significant heterogeneity. Furthermore, we identified and overcame challenges related to cell adhesion to the filter membrane and the impact of cell viability on sequencing outcomes during CTC enrichment. This workflow offers new insights into the development of CTCbased approaches for exploring tumor progression, heterogeneity, and mechanisms of drug resistance.

Early detection of lung adenocarcinoma (LUAD) remains a major clinical challenge despite the widespread application of low-dose computed tomography (LDCT). Circulating PIWI-interacting RNAs (piRNAs), characterized by tumor-specific expression and high stability, offer promise as non-invasive biomarkers. To improve the diagnostic precision of LDCT screening, we performed a large multi-center study integrating paired tissue–serum omics profiling with machine learning–based biomarker discovery. From 1,521 serum samples (1,033 LUAD, 89 benign pulmonary nodules, and 399 healthy controls), two tumor-derived PIWI-interacting RNAs (piR-hsa-8393202 and piR-hsa-8429916) were identified as highly stable, LUAD-specific molecules closely associated with disease progression. A 2-piRNA diagnostic signature demonstrated robust performance for early-stage LUAD (training AUC = 0.918; validation AUC = 0.863) and adenocarcinoma in situ (training AUC = 0.902; validation AUC = 0.907). Notably, when applied to LDCT-detected indeterminate pulmonary nodules, this signature significantly improved malignant nodule identification (AUC = 0.883), outperforming conventional serum biomarkers such as carcinoembryonic antigen and cytokeratin 19 fragment antigen 21–1. Functional assays further revealed that these piRNAs promote tumor cell proliferation and suppress apoptosis, supporting their oncogenic activity. Collectively, this study establishes circulating piRNAs as non-invasive and mechanistically relevant biomarkers for molecular stratification of pulmonary nodules within LDCT screening programs, providing a clinically applicable tool to refine early lung cancer diagnosis and guide individualized management.

Accurate detection of circulating tumor cells (CTCs) remains a critical challenge in clinical oncology due to limitations in sensitivity, cost-effectiveness, and operational complexity. In this study, a wireless cytosensor is developed, leveraging a bionic dandelion isothermal amplification system (BDIAS) and wireless lateral flow immunoassay (LFIA) technology. The BDIAS, composed of a hexapod DNAwalker, nonlinear DNA self-assembly technology and an asymmetric carrier, and AuFe Janus nanoparticles (AuFe JNPs) with high signal probe loading efficiency, exhibits remarkable amplification efficiency. Compared with traditional isothermal amplification systems (TIASs), the BDIAS demonstrated a 6.72-fold enhancement in amplification efficiency. The wireless LFIA analysis technology, integrating a wireless fluorescence strip analyzer and smartphone, enables rapid and precise detection of fluorescence signals on the test line (T-line) of the LFIA strip, with interpretation of the results completed within one second. The wireless cytosensor, based on the synergistic integration of BDIAS and wireless LFIA technology, achieves an ultralow detection limit of 1.58 cells/mL while exhibiting remarkable operational simplicity. Furthermore, it demonstrates superior specificity and reproducibility. Notably, the proposed wireless cytosensor is capable of accurately detecting CTCs in whole-blood samples and exhibits robust anti-interference capabilities, rendering it highly promising for clinical applications.

BACKGROUND:Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide, with early diagnosis critical for improving outcomes. Current diagnostic tools, including serum biomarkers and imaging techniques, exhibit limited sensitivity and specificity. Although extracellular vesicles (EVs) have emerged as a promising source of cancer biomarkers, their clinical utility is hampered by inefficient enrichment technologies.To overcome this limitation, a microfluidic platform was developed to enable rapid and efficient EV capture. RESULTS:The 3D DynaMag-EV capture chip was developed, integrating active and passive micromixing strategies for efficient capture of plasma-derived EVs. This platform employs tentacle-like magnetic particles conjugated with aptamers as the capture matrix, in combination with a 3D porous chip structure and an alternating, non-uniform magnetic field, thereby significantly enhancing EVs-capture substrate interactions and effectively addressing the limitations in collision efficiency and mass transfer. The 3D DynaMag-EV capture chip enabled rapid EV enrichment within 20 minutes, achieving high capture efficiency and purity.Transcriptome analysis of plasma EVs enriched by the developed chip identified two HCC-specific long non-coding RNAs (KCNQ1-AS1 and LINC01785) in HCC, liver cirrhosis or hepatitis patients, and healthy controls. A diagnostic model based on these two markers (EVlncRNA score) demonstrated robust performance, achieving an area under the curve (AUC) exceeding 0.80 in all cohorts and surpassing alpha-fetoprotein (AFP). Considering the accessibility of routine clinical laboratory indicators, a multiparametric diagnostic model was further developed by integrating the EVlncRNA score with conventional clinical variables (patient age, AFP , gamma-glutamyl transferase, and albumin levels) using machine learning, which enhanced the diagnostic accuracy (AUC>0.90). CONCLUSION:This study developed an integrated microfluidic platform for rapid EV isolation and established an EVlncRNA Score model, enabling highly efficient early HCC detection, even in AFP-negative cases. A multiparametric diagnostic model further improved accuracy, offering a promising tool for clinical HCC screening. This strategy presents a robust, non-invasive liquid biopsy strategy with significant potential for early HCC detection.

Introduction: Clostridium perfringens sepsis is a rare but serious clinical syndrome that is typically triggered by gastrointestinal disorders. We present a case of bloodstream infection caused by Clostridium perfringens in a liver cancer patient after comprehensive multicourse treatment. Case presentations: The patient, a 68-year-old male, experienced nausea, decreased appetite, and abdominal distension on the 15th day after receiving comprehensive multicourse treatment and transcatheter arterial chemoembolization (TACE). During admission, he developed fever, and blood culture results confirmed the presence of Clostridium perfringens. The patient was discharged with improved symptoms. Conclusion: Our findings underscore the rarity of Clostridium perfringens sepsis. For liver cancer patients, particularly those who have undergone TACE or radiofrequency ablation and who experience post treatment fever, vigilance for Clostridium perfringens bloodstream infection is crucial. Timely diagnostic assessments and proactive treatment can significantly enhance the survival prospects of these patients.

Pancreatic ductal adenocarcinoma (PDAC) is a common digestive system tumor with high mortality rates and a poor prognosis. Reports suggest that microRNA (miR)-486-3p in PDAC can be used as a diagnostic biomarker. This research aimed to elucidate the mechanisms by which miR-486-3p regulates PDAC progression. miR-486-3p and chymotrypsin C (CTRC) expression in PDAC were measured using quantitative real-time polymerase chain reaction. Changes in the biological properties of PDAC cells were assessed by Transwell assay, scratch-wound assay, cell counting kit (CCK)-8 assay, and plate cloning assay. The protein expression of immunosuppressive factors (vascular endothelial growth factor, interleukin-6, and transforming growth factor-β) in PDAC cells was detected by western blot. Additionally, a subcutaneous graft tumor model was constructed to explore the influence of silencing miR-486-3p on PDAC in vivo. PDAC showed a pronounced increase in miR-486-3p expression. Upregulation of miR-486-3p stimulated PDAC cell proliferation, migration, invasion, and immunosuppressive factor protein expression, whereas silencing miR-486-3p hindered PDAC malignant development. miR-486-3p targets and negatively regulates CTRC expression. Silencing CTRC partially rescued the restraining impact of silencing miR-486-3p on PDAC malignant progression. In vivo experiments also indicated that silencing miR-486-3p inhibited PDAC malignant progression and immunosuppressive factor expression in vivo. In summary, miR-486-3p promotes immunosuppressive factor protein expression by targeting and negatively regulating CTRC expression, which in turn promotes PDAC malignant progression.

Colorectal cancer (CRC) is the most common digestive cancer in the world. Microsatellite stability (MSS) and microsatellite instability (MSI-high) are important molecular subtypes of CRC closely related to tumor occurrence and progression and immunotherapy efficacy. The presence of CD8+ CXCR5+ follicular cytotoxic T (TFC) cells is strongly associated with autoimmune disease and CD8+ effector function. However, the roles of TFC cells in MSI-high CRC and MSS CRC are unclear. Here, we aimed to explore the characteristics of TFC cells in CRC and compare their biological functions between MSI-high and MSS CRC. We explored the expression of TFC cell in tumor tissues and peripheral blood in our clinical cohort and public datasets. By combining single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing, we explored the potential function of TFC cells and developed a prediction model for CRC. We also compared the biological functions of these cells between MSS and MSI-high CRC and used flow cytometry and coculture experiments to explore their potential regulatory functions. TFC cell markers are downregulated in tumor tissues and patient peripheral blood vs. controls. The prediction model for CRC performed well in the training and validation cohorts (KM plot p < 0.001). MSS CRC patients exhibit enrichment of genes related to the cell cycle (MKI67) and T cell activation (CD38 and HLA-DR) and decreased enrichment of immune checkpoint markers (PD1, TIM3, and LAG3). The expression of TFC cell-related genes is positively correlated with that of CD8+IFN-γ+-related genes and closely related to that of TLS-related genes in MSS CRC. The proportion of TFC cells is positively correlated with that of CD19+CD38+ B cells in MSS CRC. The prognostic prediction model has good predictive value. In MSS CRC, TFC cells function mostly in T cell activation and the cell cycle and have low expression of immune checkpoint molecules, which may influence the effectiveness of ICB therapy. TFC cells may regulate antitumor function by regulating CD19+ CD38+ B cells and TLSs.

BACKGROUND:The harmonization status of most tumor markers (TMs) is unknown. We report a feasibility study performed to determine whether external quality assessment (EQA) programs can be used to obtain insights into the current harmonization status of the tumor markers α-fetoprotein (AFP), prostate specific antigen (PSA), carcinoembryonic antigen (CEA), cancer antigen (CA)125, CA15-3 and CA19-9. METHODS:EQA sample results provided by 6 EQA providers (INSTAND [Germany], Korean Association of External Quality Assessment Service [KEQAS, South Korea], National Center for Clinical Laboratories [NCCL, China], United Kingdom National External Quality Assessment Service [UK NEQAS, United Kingdom], Stichting Kwaliteitsbewaking Medische Laboratoriumdiagnostiek [SKML, the Netherlands], and the Royal College of Pathologists of Australasia Quality Assurance Programs [RCPAQAP, Australia]) between 2020 and 2021 were used. The consensus means, calculated from the measurement procedures present in all EQA programs (Abbott Alinity, Beckman Coulter DxI, Roche Cobas, and Siemens Atellica), was used as reference values. Per measurement procedure, the relative difference between consensus mean for each EQA sample and the mean of all patient-pool-based EQA samples were calculated and compared to minimum, desirable, and optimal allowable bias criteria based on biological variation. RESULTS:Between 19040 (CA15-3) and 25398 (PSA) individual results and 56 (PSA) to 76 (AFP) unique EQA samples were included in the final analysis. The mean differences with the consensus mean of patient-pool-based EQA samples for all measurement procedures were within the optimum bias criterion for AFP, the desirable bias for PSA, and the minimum bias criterion for CEA. However, CEA results <8 µg/L exceeded the minimum bias criterion. For CA125, CA15-3, and CA19-9, the harmonization status was outside the minimum bias criterion, with systematic differences identified. CONCLUSIONS:This study provides relevant information about the current harmonization status of 6 tumor markers. A pilot harmonization investigation for CEA, CA125, CA15-3, and CA19-9 would be desirable.

Background:Lung adenocarcinoma (LUAD) is associated with high morbidity and mortality rates. Increasing evidence indicates that neutrophil extracellular traps (NETs) play a critical role in tumor progression, metastasis and immunosuppression in the LUAD tumor microenvironment (TME). Nevertheless, the use of NET formation-related genes (NFRGs) to predict LUAD patient survival and response to immunotherapy has not been explored. Therefore, this study aimed to construct a NFRGs-based prognostic signature for stratifying LUAD patients and informing individualized management strategies. Methods:The cell composition of the LUAD TME was investigated using the single-cell sequencing data in Single-Cell Lung Cancer Atlas (LuCA). NFRGs were identified to construct a prognostic signature based on The Cancer Genome Atlas (TCGA) cohort which was validated in the Gene Expression Omnibus (GEO) dataset. The univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox regression models, receiver operating characteristic (ROC) and Brier Score were applied to assess the prognostic model. A nomogram was established to facilitate the clinical application of the risk score. The Estimation of STromal and Immune cells in MAlignant Tumor tissues (ESTIMATE) and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were utilized to assess the TME and predict immunotherapy response. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was applied to quantify the expression levels of four NFRGs in LUAD paired tissue samples. Results:Single‑cell RNA sequence analysis showed the importance of neutrophils in LUAD TME. We developed and validated a 4-NFRG (CAT, CTSG, ENO1, TLR2) prognostic signature based on TCGA and GEO cohorts, which stratified patients into high-risk and low-risk groups. Univariate and multivariate analyses showed that our risk model could independently predict the survival of LUAD patients. Patients in the low-risk group exhibited a more active immune microenvironment, lower TIDE scores, lower half-maximal inhibitory concentration (IC50) values and higher immune checkpoint molecule expression. Our risk signature could serve as a biomarker for predicting immunotherapeutic benefits. Conclusions:We developed a novel prognostic signature for LUAD patients based on NFRGs and emphasized the critical role of this signature in predicting LUAD patient survival and immunotherapy response.

Introduction: Cancer patients were more likely to be affected by the coronavirus disease 2019 (COVID-19) pandemic. Therefore, we analyzed the clinical characteristics and outcomes in cancer patients who were infected with COVID-19 to determine if they were more vulnerable to COVID-19 than non-cancer patients. Methodology: This retrospective study involved 150 cancer patients and 300 non-cancer patients with a laboratory-confirmed diagnosis of COVID-19 at the Cancer Hospital of the Chinese Academy of Medical Sciences, at the end of 2022. Multivariable analysis was carried out on the factors associated with COVID-19 severity in cancer patients. Results: Compared to the non-cancer group, the cancer group saw a notably higher number of hospitalizations and fatalities. Multivariate analysis showed that COVID-19 severity was correlated with male gender (OR: 5.60, 95% CI, 1.89-16.57), and recovery duration was longer than 10 days (OR: 3.19, 95% CI, 1.09-9.32) in the cancer group. However, the severity of COVID-19 was not made worse by the administration of systemic anticancer treatments prior to the outbreak. Conclusions: During the COVID-19 Omicron epidemic, there seemed to be some association between various antitumor therapies, treatment intervals, and COVID-19 severity. The findings of this study can potentially help allay cancer patients` fears regarding COVID-19 infection and enable them to continue with crucial therapeutic processes for the treatment of cancer.

目的 对基于生化分析平台检测CA19-9活性的胶乳免疫比浊试剂盒进行检测性能的验证研究.方法 收集2022年1月至4月期间就诊于中国医学科学院肿瘤医院的肿瘤患者315例及表观健康人43例的血清样本进行性能验证试验.参考CLSI EP15-A方案,用两种水平的质控品验证待测试剂盒的精密度;参考EP6-A方案,评价待测试剂盒的线性范围;验证血清样本的稀释准确性;参考EP7-P方案,用含特定浓度干扰物(胆红素、血红蛋白、乳糜、类风湿因子)的混合血清评价试剂盒的抗干扰能力;使用表观健康人的新鲜血清样本验证待测试剂盒的生物参考区间,使用肿瘤患者的新鲜血清比较待测试剂盒与电化学发光法检测结果的相关性和偏差.结果 精密度验证显示,两种水平质控品的批内CV和批间CV(低浓度:4.08％和4.33％;高浓度:3.01％和3.55％)均小于允许不精密度(批内CV≤6.85％和批间CV≤9.14％).在21.08～843.21U/mL的检测范围内,检测曲线呈一阶线性分布,理论值与实测值的平均百分偏倚1.57％,线性良好.本试验验证的最大稀释度为1:64倍稀释,稀释验证样本与原倍血清的相对偏移为9.11％.4.65％(2/43)的表观健康人的CA19-9测定值在参考区间之外.当血清样本中胆红素≤40mg/dL、血红蛋白≤150mg/dL、类风湿因子≤500IU/mL、脂肪乳含量≤5％时,对待测试剂的检测结果无明显干扰.对临床比对样本的Spearman相关性检验显示,待评估试剂的检测结果与电化学发光法显著相关,相关系数为0.96,阳性符合率为97.78％,阴性符合率95.00％,总符合率96.19％.结论 基于生化分析平台胶乳免疫比浊法检测CA19-9的性能良好,能够满足临床需求,但仍需从抗干扰、检测灵敏度等方面寻求进一步优化.

Following the publication of the above article, a concerned reader drew to the authors' attention that the data shown for the 'CAOV3/NC mimics' experiment in Fig. 2D on p. 443 appeared to be the same as that shown for the 'TUG1‑sh+miR‑1299 inhibitors' experiment in Fig. 4H on p. 444. The authors have examined their original data, and realize that the same data was inadvertently included in the two figures. Consequently, the corrected version of Fig. 2, featuring the correct data for the 'CAOV3/NC mimics' experiment in Fig. 2D, is shown opposite. The overall conclusions of this study were not affected by this error. All the authors agree to the publication of this corrigendum, and are grateful to the Editor of Oncology Reports for allowing them the opportunity to publish this; furthermore, they apologize to the readership for any inconvenience caused. [Oncology Reports 44: 438-448, 2020; DOI: 10.3892/or.2020.7623].