Squamous Cell Carcinoma Antigen Research Articles

Development and validation of a nomogram model for lung cancer based on radiomics artificial intelligence score and clinical blood test data.

Artificial intelligence (AI) discrimination models using single radioactive variables in recognition algorithms of lung nodules cannot predict lung cancer accurately. Hence, we developed a clinical model that combines AI with blood test variables to predict lung cancer. Between 2018 and 2021, 584 individuals (358 patients with lung cancer and 226 individuals with lung nodules other than cancer as control) were enrolled prospectively. Machine learning algorithms including lasso regression and random forest (RF) were used to select variables from blood test data, Logistic regression analysis was used to reconfirm the features to build the nomogram model. The predictive performance was assessed by performing the receiver operating characteristic (ROC) curve analysis as well as calibration, clinical decision and impact curves. A cohort of 48 patients was used to independently validate the model. The subgroup application was analyzed by pathological diagnosis. A total of 584 patients were enrolled (358 lung cancers, 61.30%,226 patients for the control group) to establish the model. The integrated model identified eight potential factors including carcinoembryonic antigen (CEA), AI score, Pro-Gastrin Releasing Peptide (ProGRP), cytokeratin 19 fragment antigen21-1(CYFRA211), squamous cell carcinoma antigen(SCC), indirect bilirubin(IBIL), activated partial thromboplastin time(APTT) and age. The area under the curve (AUC) of the nomogram was 0.907 (95% CI, 0.881-0.929). The decision and clinical impact curves showed good predictive accuracy of the model. An AUC of 0.844 (95% CI, 0.710 - 0.932) was obtained for the external validation group. The nomogram model integrating AI and clinical data can accurately predict lung cancer, especially for the squamous cell carcinoma subtype.

Significantly higher serum levels and positive rates of tumor biomarkers in patients with oral lichen planus

Background/purposeOral lichen planus (OLP) is generally considered as an oral potentially malignant disorder (OPMD). Previous studies have shown significantly higher serum carcinoembryonic antigen (CEA), squamous cell carcinoma-antigen (SCC-Ag), and ferritin levels in patients with OPMDs such as oral submucous fibrosis, oral leukoplakia, oral erythroleukoplakia, or oral verrucous hyperplasia. This study aimed to evaluate whether there were significantly higher serum levels and positive rates of CEA, SCC-Ag, and ferritin in OLP patients than in healthy control subjects. Materials and methodsThe serum CEA, SCC-Ag, and ferritin levels in 106 OLP patients and 187 healthy control subjects were measured and compared. Patients with serum CEA level ≥3 ng/mL, SCC-Ag level ≥2 ng/mL, and ferritin level ≥250 ng/mL were scored as serum positive for CEA, SCC-Ag, and ferritin, respectively. ResultsThis study found significantly higher mean serum CEA and ferritin levels in 106 OLP patients than in 187 healthy control subjects. Moreover, 106 OLP patients had significantly higher serum positive rates of CEA (12.3%) and ferritin (33.0%) than 187 healthy control subjects. Although the mean serum SCC-Ag level was higher in 106 OLP patients than in 187 healthy control subjects, the difference was not statistically significant. Of the 106 OLP patients, 39 (36.8%), 5 (4.7%), and 0 (0.0%) had serum positivities of one, two, or three tumor biomarkers including CEA, SCC-Ag, and ferritin, respectively. ConclusionOur findings indicate significantly higher serum levels and positive rates of CEA and ferritin in OLP patients than in healthy control subjects.

The combination of positive anti‑WDR1 antibodies with negative anti‑CFL1 antibodies in serum is a poor prognostic factor for patients with esophageal carcinoma.

WD repeat-containing protein 1 (WDR1) regulates the cofilin 1 (CFL1) activity, promotes cytoskeleton remodeling, and thus, facilitates cell migration and invasion. A previous study reported that autoantibodies against CFL1 and β-actin were useful biomarkers for diagnosing and predicting the prognosis of patients with esophageal carcinoma. Therefore, the present study aimed to evaluate the serum levels of anti-WDR1 antibodies (s-WDR1-Abs) combined with serum levels of anti-CFL1 antibodies (s-CFL1-Abs) in patients with esophageal carcinoma. Serum samples obtained from 192 patients with esophageal carcinoma and other solid cancers. And s-WDR1-Ab and s-CFL1-Ab titers were analyzed using the amplified luminescent proximity homogeneous assay-linked immunosorbent assay. Compared with those of healthy donors, the s-WDR1-Ab levels were significantly higher in the 192 patients with esophageal, whereas these were not significantly higher in the samples from patients with gastric, colorectal, lung, or breast cancer. In 91 patients treated with surgery, sex, tumor depth, lymph node metastasis, stage and C-reactive protein levels were significantly associated with overall survival, as determined using the log-rank test, whereas the squamous cell carcinoma antigen, p53 antibody and s-WDR1-Ab levels tended to be associated with a worse prognosis. Although no significant difference was observed in the survival between the positive and negative groups of s-WDR1-Abs or s-CFL1-Abs alone in the Kaplan-Meier test, the patients in the s-WDR1-Ab-positive and s-CFL1-Ab-negative groups exhibited a significantly poorer prognosis in the overall survival analysis. On the whole, the present study demonstrates that the combination of positive anti-WDR1 antibodies with negative anti-CFL1 antibodies in serum may be a poor prognostic factor for patients with esophageal carcinoma.

Establishment of a risk stratification model based on the combination of post-treatment serum squamous cell carcinoma antigen levels and FIGO stage of cervical cancer for treatment and surveillance decision-making

ObjectiveTo develop a risk stratification model based on the International Federation of Gynecology and Obstetrics (FIGO) staging combined with squamous cell carcinoma antigen (SCC-Ag) for the classification of patients with cervical squamous cell carcinoma (CSCC) into different risk groups.MethodsWe retrospectively reviewed the data of 664 women with stage IIA–IVB CSCC according to the 2018 FIGO staging system who received definitive radiotherapy from March 2013 to December 2017 at the department of radiation oncology of Sun Yat-sen University Cancer Center. Cutoff values for continuous variables were estimated using receiver operating characteristic curve analysis. Using recursive partitioning analysis (RPA) modeling, overall survival was predicted based on the prognostic factors determined via Cox regression analysis. The predictive performance of the RPA model was assessed using the consistency index (C-index). Intergroup survival differences were determined and compared using Kaplan–Meier analysis and the log-rank test.ResultsMultivariate Cox regression analysis identified post-treatment SCC-Ag (< 1.35 ng/mL and > 1.35 ng/mL; hazard ratio (HR), 4.000; 95% confidence interval (CI), 2.911–5.496; P < 0.0001) and FIGO stage (II, III, and IV; HR, 2.582, 95% CI, 1.947–3.426; P < 0.0001) as the independent outcome predictors for overall survival. The RPA model based on the above prognostic factors divided the patients into high-, intermediate-, and low-risk groups. Significant differences in overall survival were observed among the three groups (5-year overall survival: low vs. intermediate vs. high, 91.3% vs. 76.7% vs. 29.5%, P < 0.0001). The predictive performance of the RPA model (C-index, 0.732; 95% CI, 0.701–0.763) was prominently superior to that of post-treatment SCC-Ag (C-index, 0.668; 95% CI, 0.635–0.702; P < 0.0001) and FIGO stage (C-index, 0.663; 95% CI, 0.631–0.695; P < 0.0001).ConclusionsThe RPA model based on FIGO staging and post-treatment SCC-Ag can predict the overall survival of patients with CSCC, thereby providing a guide for the formulation of risk-adaptive treatment and individualized follow-up strategies.

Advances in Squamous Cell Carcinoma Antigen and Cervix Cancer Relationship

The squamous cell carcinoma antigen is a tumor marker that is receiving more interest due to its biological properties and importance in both pathological and normal physiological processes. Numerous clinical studies have been conducted to determine the potential function of squamous cell carcinoma antigen and its isoform complexes in clinical practice. These studies have been prompted by the fact that not only squamous cell carcinoma antigen but also circulating immune complexes of it and immunoglobulin M are involved in normal physiological and pathological processes. The therapeutic use of squamous cell carcinoma antigen as a tumor marker for either squamous carcinoma diagnosis or for monitoring the response to radiation or chemotherapy, tumor recurrence, and treatment failure are supported by prior investigations. The diagnostic or prognostic utility of squamous cell carcinoma antigen is debatable, nevertheless, as these investigations provide conflicting findings. A uniform detection method, scoring system, and cutoff level must be devised to limit clinical variability between studies and to provide a more accurate and trustworthy comparison of data. Additionally, even if the effectiveness of several approaches is equivalent, only one method should be used for the dynamic monitoring of tumor marker kinetics.

Clinical utility of pretreatment serum squamous cell carcinoma antigen for prognostication and decision-making in patients with early-stage cervical cancer.

To investigate the prognostic role of pretreatment squamous cell carcinoma antigen (SCCA) in early-stage cervical cancer (CC). We enrolled 487 cases of pathology-proven early-stage [International Federation of Gynecology and Obstetrics (FIGO) I/II] squamous or adenosquamous CC that were treated from 2012 to 2015. Restricted cubic splines (RCS) with a full Cox regression model were used to evaluate the association between SCCA levels and survival outcomes. Recursive partitioning analysis (RPA) was used to construct a risk stratification model for overall survival (OS). The performance of the RPA-based model was assessed using a receiver operating characteristic (ROC) curve. RCS analysis revealed an association between SCCA and OS and disease-free survival (DFS); SCCA ⩾2.5 ng/mL was robust for risk discrimination in our cohort. SCCA had an interaction effect with FIGO classification: Patients with FIGO I and SCCA ⩾2.5 ng/mL overlapped with those with FIGO II and SCCA < 2.5 ng/mL for OS [hazard ratio, 1.04 (95% confidence interval (CI): 0.49-2.24), p = 0.903] and DFS [1.05 (0.56-1.98), p = 0.876]. RPA modeling incorporating SCCA (<2.5 ng/mL and ⩾2.5 ng/mL) and FIGO classification divided CC into three prognostic groups: RPA I, FIGO stage I, and SCCA < 2.5 ng/mL; RPA II, FIGO stage I, and SCCA ⩾ 2.5 ng/mL, or FIGO stage II and SCCA < 2.5 ng/mL; and RPA III, FIGO stage II, and SCCA ⩾ 2.5 ng/mL; with 5-year OS of 94.0%, 85.1%, and 73.5%, respectively (p < 0.001). ROC analysis confirmed that the RPA model outperformed the FIGO 2018 stage with significantly improved accuracy for survival prediction [area under the curve: RPA versus FIGO, 0.663 (95% CI: 0.619-0.705] versus 0.621 (0.576-0.664), p = 0.045]. Importantly, the RPA groupings were associated with the efficacy of treatment regimens. Surgery followed by adjuvant treatment had a higher OS (p < 0.01) and DFS (p = 0.024) than other treatments for RPA III, whereas outcomes were comparable among treatment regimens for RPA I-II. Herein, the role of SCCA for prognostication was confirmed, and a robust clinicomolecular risk stratification system that outperforms conventional FIGO classification in early-stage squamous and adenosquamous CC was presented. The model correlated with the efficacy of different treatment regimes.

Immunohistological study of ovarian mature cystic teratoma with extremely elevated SCC antigen level

Squamous cell carcinoma (SCC) antigen is a reliable tumor marker for various cancers, including cervical cancer and lung cancer, and was recently reported to correlate with the severity of inflammatory skin diseases such as atopic dermatitis. Herein, we present a case of a 47-year-old female patient who presented with acute abdomen rupture due to a mature cystic teratoma of the ovary, approximately 11 cm in diameter on imaging examination, prompting emergency laparoscopic surgery. The patient had no symptoms of atopic dermatitis. The operative findings showed no evidence of torsion, but the membrane was partially ruptured, leading to the leakage of the cyst contents. The operation was completed after excising the adnexa and intraperitoneal lavage. The postoperative results revealed a markedly high serum SCC antigen level of 55.3 ng/dL, which was normalized at 2 months postoperatively. Postoperative histopathological examination revealed no squamous cell carcinoma component but a marked lymphocytic infiltrate under the squamous epithelium, suggesting a high degree of inflammation. Additionally, immunostaining demonstrated a cluster of differentiation (CD) 8+ lymphocyte predominance over CD4+ lymphocytes, similar to the histology of atopic dermatitis. Altogether, our findings suggest that the abnormally high SCC antigen levels might be attributed to the presence of severe inflammation in the mature cystic teratoma rather than an underlying malignancy and support the notion that SCC antigen may be a useful marker beyond its established role in cervical and lung cancers.

Expression changes and clinical significance of serum neuron-specific enolase and squamous cell carcinoma antigen in lung cancer patients after radiotherapy

To explore the changes and clinical significance of serum Neuron-Specific Enolase (NSE) and Squamous Cell Carcinoma antigen (SCC) in patients with lung cancer before and after radiotherapy. 82patients with lung cancer were treated with radiotherapy, and effective clinical intervention was given during the radiotherapy process. The patients were followed up for1year after radiotherapy and were divided into a recurrence and metastasis group (n=28) and a non-recurrence and metastasis group (n=54) according to their prognosis. Another54healthy volunteers examined in the present study's hospital during the same period were selected as the control group. To compare the changes of NSE and SCC levels in serum in patients with lung cancer at admission and after radiotherapy, and to explore their clinical significance. After intervention, NSE and SCC levels in the serum of the two groups of patients were significantly lower than those before intervention, and the levels of CD4+ and CD4+/CD8+ were significantly higher than those before intervention (p<0.05); the level of CD8+ was not significantly different from that before intervention (p > 0.05). And NSE and SCC levels in the intervention group were significantly lower than those in the routine group, the levels of CD4+, CD4+/CD8+ were significantly higher than those in the routine group (p<0.05). NSE and SCC in serum can preliminarily evaluate the effect of radiotherapy in patients with lung cancer and have a certain predictive effect on prognosis.

Clinical Value of Serum miR-106a in the Diagnosis and Prognosis of Human Papillomavirus-Positive Cervical Cancer

Introduction: Cervical cancer (CC) is a prevailing malignant tumor in women, mainly caused by human papillomavirus (HPV) infection. This study investigated miR-106a expression in the serum of HPV-positive CC patients and estimated its value in diagnosis and prognosis. Methods: We enrolled 120 CC patients as study subjects, with another 80 healthy women as controls. Clinical baseline data and clinicopathological indexes including age, tumor size, differentiation degree, FIGO stage, lymph node metastasis, and squamous cell carcinoma antigen (SCC-Ag) were recorded. Serum miR-106a expression was measured using reverse transcription-quantitative polymerase chain reaction. Receiver operating characteristic curve was employed to estimate the efficacy of miR-106a in diagnosing CC or HPV-positive CC. Under a 5-year follow-up, patient survival was recorded, and the impact of miR-106a on overall survival rate was analyzed by the Kaplan-Meier method. The logistic regression model was used to analyze whether miR-106a was an independent prognostic factor for HPV infection in CC patients. Results: Serum miR-106a was upregulated in CC patients and the level >1.365 assisted the CC diagnosis. miR-106a expression in HPV-positive CC patients was elevated relative to HPV-negative CC patients, and serum miR-106a level >1.300 distinguishing HPV positive and HPV negative. HPV positivity was linked with tumor differentiation degree, FIGO stage, lymph node metastasis, and SCC-Ag in CC patients, but not with age and tumor size. High expression of miR-106a in HPV-positive CC patients increased the risk of poor prognosis, and miR-106a expression is an independent prognostic factor for HPV infection in CC patients. Conclusion: High expression of miR-106a assists in the diagnosis of HPV-positive CC and predicts poor prognosis.

Diagnostic value of aberrant decreased 5-Methylcytosine RNA modification in leukocytes for non-small cell lung cancer.

Background: Non-small cell lung cancer (NSCLC) was a disease with poor outcomes, partly because there were no high-efficiency non-invasive diagnostic biomarkers. The RNA modification status of 5-Methylcytosine (m5C) has been shown to be a biomarker for various diseases, but its potentiality to be a diagnostic biomarker for NSCLC remained inconclusive. Methods: In this research, we collected peripheral leukocyte samples from 141 patients with NSCLC and 90 normal people as controls to evaluate the extent of m5C RNA modification. Results: We found that the m5C modification levels in leukocytes of NSCLC patients were decreased dramatically, which were compared to the normal controls, and levels of m5C modification decreased progressively with tumor stage. Importantly, m5C modification exhibited superior diagnostic value compared to carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC), cytokeratin 19 fragment (Cyfra21-1), and carbohydrate antigen 125 (CA125), which demonstrated area under the curves (AUCs) of 0.912, 0.773, 0.669, 0.754, and 0.732, respectively. The combination of m5C modification with these serum tumor biomarkers further improved the AUC to 0.960. A nomogram model incorporating m5C modification also provided an effectively diagnostic tool for NSCLC. Conclusion: Collectively, our findings suggested that m5C modification in leukocytes held promise as a prospective biomarker for NSCLC diagnosis.

A preoperative prediction of lymph node metastasis in early cervical squamous cell cancer with hematologica - based model.

Background: This study aimed to construct a preoperative model predicting lymph node metastasis (LNM) in IB1-IIA2 stage cervical squamous cell cancer (CSCC) based on hematological indexes. Merhods: Between February 2011 and February 2022, 463 patients with IB1-IIA2 stage CSCC underwent radical resection. Patients were allocated to either a model-development cohort (n=337) or a validation cohort (n=126). The final model was determined by comparing different methods of variable selection, and then its discrimination and calibration metrics were evaluated. A predicted probability of LNM < 5% was defined as low risk. ROC curves were used to define high risk. Results: Age, lactate dehydrogenase level, FIGO stage, squamous cell carcinoma antigen, cancer antigen 125, and cancer antigen 199 were identified as critical factors for the construction of the model. The model demonstrated good discrimination and calibration (concordance index, 0.761; 95% confidence interval, 0.666-0.884). In the validation cohort the discrimination accuracy was 0.821 (95% confidence interval, 0.714 - 0.927). In the model-development cohort, 11.9% were classified as low risk with a negative predictive value of 95.0%, and 24.9% were classified as high risk with a positive predictive value of 39.3%. Conclusion: A predictive model was developed and validated for LNM in IB1-IIA2 stage CSCC. The model will assist physicians in appraising the risk of LNM in preoperative patients and could aid in patient counseling and individualized clinical decision-making.

Lipopolysaccharide and statin-mediated immune-responsive protein networks revealed in macrophages through affinity purification spacer-arm controlled cross-linking (AP-SPACC) proteomics.

Toll-like receptor 4 (TLR4), a pattern recognition receptor, is activated by lipopolysaccharides (LPS) and induces the MyD88 pathway, which subsequently produces pro-inflammatory cytokines through activation of transcriptional nuclear factor (NF)-κB. Statins have been widely prescribed to reduce cholesterol synthesis for patients with cardiovascular disease. Statins may have pleiotropic effects, which include anti- and pro-inflammatory effects on cells. The molecular mechanism of the sequential influence of LPS and statin on the innate immune system remains unknown. We employed affinity purification-spacer-arm controlled cross-linking (AP-SPACC) MS-based proteomics analysis to identify the LPS- and statin-LPS-responsive proteins and their networks. LPS-stimulated RAW 264.7 macrophage cells singly and combined with the drug statin used in this study. Two chemical cross-linkers with different spacer chain lengths were utilized to stabilize the weak and transient interactors. Proteomic analysis identified 1631 differentially expressed proteins. We identified 151 immune-response proteins through functional enrichment analysis and visualized their interaction networks. Selected candidate protein-coding genes were validated, specifically squamous cell carcinoma antigens recognized by T cells 3, sphingosine-1-phosphate lyase 1, Ras-related protein Rab-35, and tumor protein D52 protein-coding genes through transcript-level expression analysis. The expressions of those genes were significantly increased upon statin treatment and decreased in LPS-stimulated macrophage cells. Therefore, we presumed that the expression changes of genes occurred due to immune response during activation of inflammation. These results highlight the immune-responsive proteins network, providing a new platform for novel investigations and discovering future therapeutic targets for inflammatory diseases.

β-Cyclodextrin-functionalized Ti3C2Tx MXene nanohybrids as innovative signal amplifiers for the electrochemical sandwich-like immunosensing of squamous cell carcinoma antigen.

Herein, a simple and highly sensitive electrochemical sandwich-like immunosensor for the squamous cell carcinoma antigen (SCCA) was constructed using gold nanoparticle/graphene nanosheet (Au/GN) nanohybrids as a sensing platform and β-cyclodextrin/Ti3C2Tx MXenes (β-CD/Ti3C2Tx) as a signal amplifier. The good biocompatibility and large surface area as well as the high conductivity of Au/GN allow the platform to load primary antibodies (Ab1) and facilitate electron transport. In the case of the β-CD/Ti3C2Tx nanohybrids, the β-CD molecule is dedicated to binding secondary antibodies (Ab2) through host-guest interactions, thus inducing the formation of the sandwich-like structure Ab2-β-CD/Ti3C2Tx/SCCA/Ab1/Au/GN in the presence of SCCA. Interestingly, Cu2+ can be adsorbed and self-reduced on the surface of the sandwich-like structure to form Cu0 since Ti3C2Tx MXenes can exhibit superior adsorption and reduction capabilities towards Cu2+, and a prominent current signal of Cu0 can be observed via differential pulse voltammetry. Based on this principle, an innovative signal amplification strategy has been proposed for SCCA detection, which avoids the process of labeling the probe and the specific immobilization step of catalytic components on the surface of amplification markers. After the optimization of various conditions, a wide linear range from 0.05 pg mL-1 to 20.0 ng mL-1, coupled with a low detection limit of 0.01 pg mL-1, was obtained for SCCA analysis. The proposed method for SCCA detection was also applied in real human serum samples and the observed results are satisfactory. This work opens up new pathways for constructing electrochemical sandwich-like immunosensors for SCCA and other targets.

RESOLVE-DWI-based deep learning nomogram for prediction of normal-sized lymph node metastasis in cervical cancer: a preliminary study

BackgroundIt is difficult to predict normal-sized lymph node metastasis (LNM) in cervical cancer clinically. We aimed to investigate the feasibility of using deep learning (DL) nomogram based on readout segmentation of long variable echo-trains diffusion weighted imaging (RESOLVE-DWI) and related patient information to preoperatively predict normal-sized LNM in patients with cervical cancer.MethodsA dataset of MR images [RESOLVE-DWI and apparent diffusion coefficient (ADC)] and patient information (age, tumor size, International Federation of Gynecology and Obstetrics stage, ADC value and squamous cell carcinoma antigen level) of 169 patients with cervical cancer between November 2013 and January 2022 were retrospectively collected. The LNM status was determined by final histopathology. The collected studies were randomly divided into a development cohort (n = 126) and a test cohort (n = 43). A single-channel convolutional neural network (CNN) and a multi-channel CNN based on ResNeSt architectures were proposed for predicting normal-sized LNM from single or multi modalities of MR images, respectively. A DL nomogram was constructed by incorporating the clinical information and the multi-channel CNN. These models’ performance was analyzed by the receiver operating characteristic analysis in the test cohort.ResultsCompared to the single-channel CNN model using RESOLVE-DWI and ADC respectively, the multi-channel CNN model that integrating both two MR modalities showed improved performance in development cohort [AUC 0.848; 95% confidence interval (CI) 0.774–0.906] and test cohort (AUC 0.767; 95% CI 0.613–0.882). The DL nomogram showed the best performance in development cohort (AUC 0.890; 95% CI 0.821–0.938) and test cohort (AUC 0.844; 95% CI 0.701–0.936).ConclusionThe DL nomogram incorporating RESOLVE-DWI and clinical information has the potential to preoperatively predict normal-sized LNM of cervical cancer.

Prevalent distribution and survival outcome of HPV infection in patients with early-stage cervical cancer in Hangzhou, China

ObjectivesTo describe the prevalent distribution of human papilloma virus (HPV) infection in patients with early-stage cervical squamous cell carcinoma (CSCC). To provide data on high-risk HPV (HR-HPV) infection and other clinicopathological factors for their correlations with the survival of CSCC patients.MethodsA total of 1425 patients with FIGO stages IA to IIA CSCC who underwent radical surgery between September 2008 and December 2012 were enrolled in the study. The prevalent distribution of HPV infection with different patient characteristics and survivals were analyzed with or without propensity score matching (PSM).ResultsThe overall infection rate of HPV was 84.3%, including 13 carcinogenic HR-HPV genotypes and 8 low-risk HPV genotypes with infection rates of 82.6% and 5.8%, respectively. The distribution of HPV infection were proportional in patients with either different age groups or different FIGO stages. HPV16 was the dominant subtype with an infection rate of 65.1%, followed by the other top four subtypesHPV58 (8.7%), 18 (7.7%) and 52 (4.5%). χ2 analysis revealed that increased preoperative serum squamous cell carcinoma antigen levels and lymphovascular space invasion (LVSI) were statistically associated with HPV status. However, regression analyses indicated that only deep stromal invasion, LVSI and lymph node metastasis were independent prognostic factors on 5-year overall survival (OS), but not HR-HPV infection status even in the second exploratory analysis (P = 0.939) based on the PSM applied to reduce selection bias.ConclusionsThis study provided baseline data on the prevalence characteristics of HPV infections in patients with early-stage CSCC, and HR-HPV infection was not a prognosticator of 5-year OS, other than FIGO stage, LVSI and lymph node metastasis.

Immunohistochemical Analysis of Common Cancer Antigens in Head and Neck Squamous Cell Carcinoma

The prognosis of recurring and metastatic head and neck squamous cell carcinoma (HNSCC) is poor. Although immune checkpoint inhibitors have expanded the treatment options for HNSCC, the response rates are low. Alternatively, cancer vaccines and T-cell therapies are being developed. Identification of useful common cancer antigens and confirmation of human leukocyte antigen (HLA) class I expression are required. Immunohistochemistry analyses were performed for 10 antigens (FOXM1, TGFBI, SPARC, HSP105α, WT1, AFP, GPC3, PP-RP, KIF20A, KM-HN-1) and HLA class I using specimens of 56 surgical cases. Staining intensity, percentage of stain-positive areas, and localization of staining in the tumor cells and normal tissue were evaluated. Staining of FOXM1, TGFBI, SPARC, and HSP105α was more predominant in tumor cells than that in normal cells. The expression rates of these antigens in tumor cells were 60.7%, 58.9%, 73.2%, and 50.0%, respectively. Regarding sites, the expression rates of these antigens in oral cancer were high at 57.1%, 71.4%, 81.0%, and 66.7%, respectively. Furthermore, the expression of HLA class I was 83.9% in all cases. Of these, 68.1% showed expression on the plasma membrane. FOXM1, TGFBI, SPARC, and HSP105α could be useful common cancer antigens, and HLA class I is expressed on the plasma membrane of cancer cells in many cases. The results suggest that cancer vaccines and T-cell therapy may be clinically viable options for HNSCC treatment.

474 Increased Expression of Squamous Cell Carcinoma Antigen 1 and 2 in Mycosis Fungoides and Sézary Syndrome

Mycosis fungoides (MF) and Sézary syndrome (SS) are classical types of cutaneous T-cell lymphoma (CTCL). MF is the most common type of CTCL, which is characterized by malignant proliferation of neoplastic CD4+ T cells with epidermotropism in the skin. SS is an aggressive leukemic type of CTCL characterized by a triad of erythroderma, lymphadenopathy and leukemic involvement. Squamous cell carcinoma antigen (SCCA) was originally isolated as tumor-specific antigens. SCCA comprises 2 proteins, SCCA1 and SCCA2, and both are induced by type 2 cytokines.

Potential biomarkers of atopic dermatitis.

Atopic dermatitis (AD) is a chronic, recurrent inflammatory skin disease with a wide range of heterogeneity. Accurate biomarkers or predictors are the keys to instructing personalized tailored precise treatment. The development of technology such as transcriptomics, genomics, and proteomics provides novel insights into the possibility to find potential biomarkers. Meanwhile, emerging minimally invasive methods such as tape stripping were used to reveal different profiles of patients' skin without biopsy. Several potential biomarkers or predictors have been found. In this review, we summarized the current development of potential biomarkers of AD. Nitric oxide synthase 2/inducible nitric oxide synthase (NOS2/iNOS), human beta-defensin-2 (hBD-2), and matrix metalloproteinases 8/9 (MMP8/9) may be the candidate biomarkers for AD diagnosis. Filaggrin (FLG) gene mutation increased the occurrence risk of AD. Fatty-acid-binding protein 5 (FABP5) may serve as an effective biomarker for the atopic march (AM). Squamous cell carcinoma antigen 2 (SCCA2), serum thymus and activation-regulated chemokine (TARC), cutaneous T-cell-attracting chemokine (CTACK), eosinophil-derived neurotoxin (EDN), macrophage-derived chemokine (MDC), lactate dehydrogenase (LDH), and interleukin (IL)-18 can be the candidate biomarkers for disease severity monitoring. IL-17, IL-23, IL-33, and indoleamine 2,3-dioxygenase (IDO1) can be used as predictive biomarkers for AD comorbidities. LDH, TARC, pulmonary and activation-regulated chemokine (PARC), periostin, IL-22, eotaxin-1/3, and IL-8 may be the candidate biomarkers for monitoring treatment effects. There are still unmet needs and a long way to go for more convenient, non-invasive, and effective predictors and biomarkers to better guide personalized precise treatment.

Effect of Renshen Yangying Decoction Combined with Chemotherapy on Traditional Chinese Medical Symptoms and T Cell Subsets in Patients with Cervical Cancer of Ganyu Qizhi Type

Background To confirm the effects of the combination of Renshen Yangying decoction and chemotherapy on traditional Chinese medical symptoms and T cell subsets in patients with cervical cancer (CC) of Ganyu Qizhi type.Methods: Patients with CC of Ganyu Qizhi type admitted to our hospital (n=96) were selected and evenly divided into control and observation groups. The patients in control group received chemotherapy, while those in observation group were additionally treated with Renshen Yangying decoction. The clinical efficacy, traditional Chinese medical symptom (TCMS) score, serum tumor markers, changes of serum T lymphocyte subsets and adverse effects were compared.Results: The distribution of clinical efficacy grade in all patients after treatment was statistically significant, and the clinical benefit rate (CBR) of observation group was higher than that of control group. The TCMS score, the serum carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCCA), and cancer antigen 125 (CA125) were also decreased after treatment, and those were decreased in observation group. Levels of serum CD4+ and CD4+/CD8+, and natural killer (NK) cell percentage were higher, yet serum CD8+ cell percentage was lower after treatment, and in patients of observation group, levels of serum CD4+ and CD4+/CD8+, and NK cell percentage were higher, yet serum CD8+ cell percentage was lower. The incidence of adverse effects in the observation group was lower than that in the control group.Conclusion: Renshen Yangying decoction combined with chemotherapy in the treatment of CC of Ganyu Qizhi type can alleviate the clinical symptoms, reduce serum tumor markers, and improve the cellular immunity, with significant clinical efficacy and good safety on patients.

Bimetallic PtFe alloyed nanoparticles decorated on 3D hollow N-doped carbon nanoflowers as efficient electrochemical biosensing interfaces for ultrasensitive detection of SCCA

Recently, cervical cancer seriously threatens women’s health and life, where squamous cell carcinoma antigen (SCCA) is a representative biomarker widely applied for the early diagnosis and therapy. Herein, bimetallic PtFe alloyed nanoparticles were efficiently decorated on three-dimensional hollow N-doped carbon nanoflowers (PtFe/H-NCFs) by a simple pyrolysis strategy. We strictly investigated the influences of the hollow nanoflower-like structure, N-doping and highly active PtFe nanoalloys on the detection signals from Fe(CN) 6 3– oxidation, coupled with their effects on the loading of the SCCA antibody. Consequently, a high-performance label-free PtFe/H-NCFs-based biosensor was established for ultrasensitive analysis of SCCA, with a wider linear range of 0.01 pg mL –1 -10 ng mL –1 and a lower limit of detection (0.003 pg mL –1 , S/N = 3). The developed sensor holds potential applications for monitoring biomarkers in early diagnosis and clinic therapy. • PtFe/H-NCFs with large surface area were prepared by a one-pot pyrolysis strategy. • PtFe nanoparticles were well decorated on the 3D H-NCFs, showing high electrocatalytic activity. • The prepared immunosensor showed highly improved analytical performance for detecting SCCA.