Tumor autoantibodies as biomarkers for predicting ovarian cancer recurrence

Identification of novel serum autoantibody biomarkers for early esophageal squamous cell carcinoma and high-grade intraepithelial neoplasia detection

Background

Early diagnosis of esophageal squamous cell carcinoma (ESCC) is critical for effective treatment and optimal prognosis; however, less study on serum biomarkers for the early ESCC detection has been reported. The aim of this study was to identify and evaluate several serum autoantibody biomarkers in early ESCC.

Methods

We initially screened candidate tumor-associated autoantibodies (TAAbs) associated with ESCC by serological proteome analysis (SERPA) combined with nanoliter-liquid chromatography combined with quadrupole time of flight tandem mass spectrometry (nano-LC-Q-TOF-MS/MS), and the TAAbs were further subjected to analysis by Enzyme-linked immunosorbent assay (ELISA) in a clinical cohort (386 participants, including 161 patients with ESCC, 49 patients with high-grade intraepithelial neoplasia [HGIN] and 176 healthy controls [HC]). Receiver operating characteristic (ROC) curve was plotted to evaluate the diagnostic performance.

Results

The serum levels of CETN2 and POFUT1 autoantibodies which were identified by SERPA were statistically different between ESCC or HGIN patients and HC in ELISA analysis with the area under the curve (AUC) values of 0.709 (95%CI: 0.654-0.764) and 0.741 (95%CI: 0.689-0.793), 0.717 (95%CI: 0.634-0.800) and 0.703 (95%CI: 0.627-0.779) for detection of ESCC and HGIN, respectively. Combining these two markers, the AUCs were 0.781 (95%CI: 0.733-0.829), 0.754 (95%CI: 0.694-0.814) and 0.756 (95%CI: 0.686-0.827) when distinguishing ESCC, early ESCC and HGIN from HC, respectively. Meanwhile, the expression of CETN2 and POFUT1 was found to be correlated with ESCC progression.

Conclusions

Our data suggest that CETN2 and POFUT1 autoantibodies have potential diagnostic value for ESCC and HGIN, which may provide novel insights for early ESCC and precancerous lesions detection.

Autoantibodies against cytoskeletons and lysosomal trafficking discriminate sarcoidosis from healthy controls, tuberculosis and lung cancers

Sarcoidosis is a systemic granulomatous disease of unknown etiology. Hypergammaglobulinemia and the presence of autoantibodies in sarcoidosis suggest active humoral immunity to unknown antigen(s). We developed a complex cDNA library derived from tissues of sarcoidosis patients. Using a high throughput method, we constructed a microarray platform from this cDNA library containing large numbers of sarcoidosis clones. After selective biopanning, 1070 sarcoidosis-specifc clones were arrayed and immunoscreend with 152 sera from patients with sarcoidosis and other pulmonary diseases. To identify the sarcoidosis classifiers two statistical approaches were conducted: First, we identified significant biomarkers between sarcoidosis and healthy controls, and second identified markers comparing sarcoidosis to all other groups. At the threshold of an False Discovery Rate (FDR) < 0.01, we identified 14 clones in the first approach and 12 clones in the second approach discriminating sarcoidosis from other groups. We used the classifiers to build a naïve Bayes model on the training-set and validated it on an independent test-set. The first approach yielded an AUC of 0.947 using 14 significant clones with a sensitivity of 0.93 and specificity of 0.88, whereas the AUC of the second option was 0.92 with a sensitivity of 0.96 and specificity of 0.83. These results suggest robust classifier performance. Furthermore, we characterized the informative phage clones by sequencing and homology searches. Large numbers of classifier-clones were peptides involved in cellular trafficking and cytoskeletons. These results show that sarcoidosis is associated with a specific pattern of immunoreactivity that can discriminate it from other diseases.

Evaluation of paraneoplastic antigens reveals TRIM21 autoantibodies as biomarker for early detection of ovarian cancer in combination with autoantibodies to NY-ESO-1 and TP53

BACKGROUND

The majority of ovarian cancer cases are diagnosed at an advanced stage with poor prognosis. This study evaluates autoantibodies against tumor antigens to identify candidate biomarkers for early detection of ovarian cancer in women at increased risk.

OBJECTIVE

To assess the immunoreactivity of paraneoplastic antigens and tumor associated antigens with high-grade serous ovarian cancer (HGSOC) samples.

METHODS

Five paraneoplastic antigens along with three tumor-associated antigens were evaluated with HGSOC patient serum samples. Validation screening was performed with n= 164 serum samples consisting of: 50 late stage HGSOC, 14 early stage HGSOC, 50 benign ovarian cyst, and 50 healthy control samples on ELISA and western blot. The four markers TRIM21, NY-ESO-1, TP53, and PAX8 were evaluated on a second validation serum set, n= 150.

RESULTS

TRIM21 achieved the highest sensitivity in the first validation screening of 33% with 100% specificity. Combining TRIM21 with NY-ESO-1, TP53, and PAX8 provided 67% sensitivity with 94% specificity, and 56% sensitivity at 98% specificity. These four markers resulted in 46% sensitivity with 98% specificity in the second validation cohort; TRIM21 achieved the highest individual sensitivity of 36%.

CONCLUSIONS

Autoantibodies to TRIM21, NY-ESO-1, and TP53 may complement CA125 in screening of women at genetic risk for ovarian cancer.

Serum folate receptor α (sFR) in ovarian cancer diagnosis and surveillance

Novelty and Impact Statement: Our findings suggest that soluble folate receptor (sFR) could be used in both the initial diagnosis and surveillance of patients with ovarian cancer. Our cohort constitutes one of the largest comparison groups for sFR analyzed so far. We have defined the background level of sFR using healthy volunteers. This is also the first study to prospectively follow patients in the surveillance setting to concurrently identify differential changes in tumor markers CA-125 and sFR.

Serum folate receptor α (sFR) in ovarian cancer diagnosis and surveillance

Novelty and Impact Statement: Our findings suggest that soluble folate receptor (sFR) could be used in both the initial diagnosis and surveillance of patients with ovarian cancer. Our cohort constitutes one of the largest comparison groups for sFR analyzed so far. We have defined the background level of sFR using healthy volunteers. This is also the first study to prospectively follow patients in the surveillance setting to concurrently identify differential changes in tumor markers CA-125 and sFR.

Serum folate receptor α (sFR) in ovarian cancer diagnosis and surveillance

Novelty and Impact Statement: Our findings suggest that soluble folate receptor (sFR) could be used in both the initial diagnosis and surveillance of patients with ovarian cancer. Our cohort constitutes one of the largest comparison groups for sFR analyzed so far. We have defined the background level of sFR using healthy volunteers. This is also the first study to prospectively follow patients in the surveillance setting to concurrently identify differential changes in tumor markers CA‐125 and sFR.

Utility of paraneoplastic antigens as biomarkers for surveillance and prediction of recurrence in ovarian cancer

BACKGROUND

Ovarian cancer is frequently diagnosed at an advanced stage and 70% of patients experience recurrence months to years from initial diagnosis. The expression of paraneoplastic antigens can result in the occurrence of onconeural autoantibodies in ovarian cancer that may be associated with neurological disorders that are clinically manifested in patients before diagnosis of ovarian cancer. These paraneoplastic antigens can serve as excellent biomarkers not only for early detection but also for monitoring ovarian cancer recurrence.

OBJECTIVE

To assess the immunoreactivity of our previous 3 biomarkers along with 3 paraneoplastic antigens, HARS, Ro52 and CDR2 for the evaluation of their sensitivity in predicting recurrence before the clinical relapse of the ovarian cancer.

METHODS

Western blot immunoassays were performed to assess the immunoreactivity of 6 antigens with 21 recurrent ovarian cancer patients.

RESULTS

The results indicated that antibodies to HARS, Ro52, CDR2 and 5H6 antigens predicted ovarian cancer recurrence 5.03 months before the clinical or symptomatic relapse in 21 ovarian cancer patients with a sensitivity of 90.5% when CA125 levels were below the standard cutoff (35 U/ml).

CONCLUSION

Our study suggests that appearance of onconeural antibodies prior to the rise in CA125 during post treatment surveillance can be a useful diagnostic to predict ovarian cancer recurrence.

Paraneoplastic antigens as biomarkers for early diagnosis of ovarian cancer

Paraneoplastic syndromes are a group of rare disorders that can be triggered by an abnormal immune response to proteins from tumors of the lung, ovary, lymphatics, or breast. Paraneoplastic clinical syndromes affect < 1% of patients with cancer; however, the frequency of subclinical levels of paraneoplastic autoantibodies in asymptomatic patients with cancer is unknown. Numerous studies have reported that ovarian cancer patients show signs of paraneoplastic neurological syndromes (PNSs) before or after their cancers are diagnosed. PNSs arise from a tumor-elicited immune response against onconeural antigens that are shared by tissues of nervous system, muscle, and tumor cells. Studies on the serum IgGs obtained from ovarian cancer patients have indicated the presence of onconeural antibodies in the absence of any PNS symptoms. The occurrence of PNSs is low in ovarian cancer patients and it can be accompanied by onconeural antibodies. The diagnosis of PNSs is accompanied by a suspicion of a malignant tumor such that neurologists typically refer such patients for a tumor diagnostic workup. There will be tremendous utility if subclinical levels (without paraneoplastic neurological symptoms or myositis) of these autoantibodies to paraneoplastic antigens can be exploited to screen asymptomatic high-risk patients for ovarian cancer, and used as biomarkers in immunoassays for the early detection or recurrence of ovarian cancer. Ovarian cancer overall survival is likely to be improved with early detection. Therefore, a panel of onconeural antigens that can detect paraneoplastic autoantibodies in patient sera should provide diagnostic utility for an earlier therapeutic intervention. Here we review the usefulness of PNS and other paraneoplastic syndromes and their association with paraneoplastic antigens to exploit these autoantibody biomarkers to form diagnostic multi-analyte panels for early detection of ovarian cancer.

Recurrence prediction in oral cancers: a serum Raman spectroscopy study

High mortality rates associated with oral cancers can be primarily attributed to the failure of current histological procedures in predicting recurrence. Identifying recurrence related factors can lead to improved prognosis, optimized treatment and enhanced overall outcomes. Serum Raman spectroscopy has previously shown potential in the diagnosis of cancers, such as head and neck, cervix, breast, oral cancers, and also in predicting treatment response. In the present study, serum was collected from 22 oral cancer subjects [with recurrence (n = 10) and no-recurrence (n = 12)] before and after surgery and spectra were acquired using a Raman microprobe coupled with a 40× objective. Spectral acquisition parameters were as follows: λex = 785 nm, laser power = 30 mW, integration time: 12 s and averages: 3. Data was analyzed in a patient-wise approach using unsupervised PCA and supervised PC-LDA, followed by LOOCV. PCA and PC-LDA findings suggest that recurrent and non-recurrent cases cannot be classified in before surgery serum samples; an average classification efficiency of ∼78% was obtained in after-surgery samples. Mean and difference spectra and PCA loadings indicate that DNA and protein markers may be potential spectral markers for recurrence. RS of post surgery serum samples may have the potential to predict the probability of recurrence in clinics, after prospective large-scale validation.