3-marker Panel Research Articles

DNA Methylation and p53 Immunohistochemistry as Prognostic Biomarkers for Vulvar Lichen Sclerosus

Vulvar lichen sclerosus (LS) is an inflammatory dermatosis that can progress to human papillomavirus (HPV)-independent vulvar intraepithelial neoplasia (HPVi VIN) and vulvar squamous cell carcinoma (VSCC). Although LS has a much lower cancer risk compared with HPVi VIN (5% vs 50%, respectively), its incidence is significantly higher. Therefore, there is a clinical need to identify LS patients with an increased cancer risk. Our objective was to study the value of DNA methylation and p53 immunohistochemistry (IHC) as prognostic biomarkers for progression to cancer in patients with LS. Vulvar tissues from 236 patients were selected, including 75 LS and 68 HPVi VIN, both with and without cancer development, 32 VSCC, and 61 healthy vulvar controls. Samples were subjected to p53 IHC and DNA methylation analysis of a 3-gene marker panel containing ZNF582, SST, and miR124-2. Methylation levels and p53 IHC status (mutant or wild-type) were assessed and compared among all disease categories. Odds ratios were determined to identify whether the biomarkers were associated with progression to cancer in patients with LS. The highest methylation levels were found in HPVi VIN and VSCC, followed by LS and healthy vulvar controls. The largest heterogeneity in methylation levels was observed in LS cases. In fact, the 3-marker panel tested positive in 70% of LS, which progressed to VSCC vs only 17% of LS in patients without cancer development (P = .002). Also, mutant p53 IHC was observed more frequently in LS with progression to VSCC compared with nonprogressive LS cases (42% vs 3%, respectively, P = .001). Multivariable analysis identified a mutant p53 status as the only independent risk factor for cancer development in LS (odds ratio: 34.0, 95% CI: 1.4-807.4). In conclusion, DNA methylation testing and p53 IHC show strong potential as prognostic biomarkers for the identification of LS patients at high risk of progression to cancer.

Predictive three-biomarker panel in peripheral blood mononuclear cells for detecting hepatocellular carcinoma

Hepatocellular carcinoma (HCC) ranks among the most prevalent cancers and accounts for a significant proportion of cancer-associated deaths worldwide. This disease, marked by multifaceted etiology, often poses diagnostic challenges. Finding a reliable and non-invasive diagnostic method seems to be necessary. In this study, we analyzed the gene expression profiles of 20 HCC patients, 12 individuals with chronic hepatitis, and 15 healthy controls. Enrichment analysis revealed that platelet aggregation, secretory granule lumen, and G-protein-coupled purinergic nucleotide receptor activity were common biological processes, cellular components, and molecular function in HCC and chronic hepatitis B (CHB) compared to healthy controls, respectively. Furthermore, pathway analysis demonstrated that “estrogen response” was involved in the pathogenesis of HCC and CHB conditions, while, “apoptosis” and “coagulation” pathways were specific for HCC. Employing computational feature selection and logistic regression classification, we identified candidate genes pivotal for diagnostic panel development and evaluated the performance of these panels. Subsequent machine learning evaluations assessed these panels’ performance in an independent cohort. Remarkably, a 3-marker panel, comprising RANSE2, TNF-α, and MAP3K7, demonstrated the best performance in qRT-PCR-validated experimental data, achieving 98.4% accuracy and an area under the curve of 1. Our findings highlight this panel’s promising potential as a non-invasive approach not only for detecting HCC but also for distinguishing HCC from CHB patients.

Glomerular Filtration Rate Estimation Using β2-Microglobulin and β-Trace Protein in Adults With Solid Tumors: A Prospective Cross-Sectional Study

β2-Microglobulin (B2M) and β-trace protein (BTP) are novel endogenous filtration markers that may improve the accuracy of estimated glomerular filtration rate (eGFR) beyond creatinine and cystatin C (eGFRcr-cys), but they have not been assessed in patients with cancer. Cross-sectional analysis. Prospective cohort of 1,200 patients with active solid tumors recruited between April 2015 and September2017. CKD-EPI equations without race combining B2M and/or BTP with creatinine with or without cystatin C (2-, 3-, or 4-marker panel eGFR). Performance of equations compared with eGFRcr-cys and non-GFR determinants of serum B2M and BTP (SB2M, and SBTP, respectively). Measured GFR (mGFR) was determined using the plasma clearance of chromium-51 labeled ethylenediamine tetraacetic acid (51Cr-EDTA). Bias was defined as the median of the differences between mGFR and eGFR, and 1-P30 was defined as the percentage of estimates that differed by more than 30% from the mGFR (1-P30). Linear regression was used to assess association of clinical and laboratory variables with SB2M, and SBTP after adjustment for mGFR. Mean age and mGFR were 58.8±13.2 SD years and 78.4±21.7 SD mL/min/1.73m2, respectively. Performance of the 3-marker and 4-marker panel equations was better than eGFRcr-cys (lesser bias and 1-P30). Performance of 2-marker panel equations was as good as eGFRcr-cys (lesser bias and similar 1-P30). SB2M and SBTP were not strongly influenced by cancer site. Participants may have had better clinical performance status than the general population of patients with solid tumors. B2M and BTP can improve the accuracy of eGFR and may be useful as confirmatory tests in patients with solid tumors, either by inclusion in a multimarker panel equation with creatinine and cystatin C, or by substituting for cystatin C in combination with creatinine. The most accurate method to assess estimate kidney function is estimated glomerular filtration rate (eGFR) using creatinine and cystatin C (eGFRcr-cys). We studied whether using β2-microglobulin (B2M) and/or β-trace protein (BTP) with creatinine with or without cystatin C (2-, 3-, or 4-marker panel eGFR) might be useful in patients with active solid tumors. The performance of the 3-marker and 4-marker panel equations was better than eGFRcr-cys. Performance of 2-marker panel equations was as good as eGFRcr-cys. We conclude that B2M and BTP can improve the accuracy of eGFR and may be useful as a confirmatory test in patients with solid tumors either by inclusion in multimarker panel equation with creatinine and cystatin C or by substituting for cystatin C in combination with creatinine.

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery

The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma. Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n=53) and without (n=65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony. A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively. Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted. Cancer Research UK, Blood Cancer UK, National Institute for Health Research.

Predicting Progestin Therapy Response With PTEN, PAX2, and β-Catenin in Patients With Endometrioid Precancer.

This study investigates the predictive value of biomarkers PTEN, PAX2, and β-catenin for therapeutic outcomes in patients with atypical endometrial hyperplasia or endometrioid intraepithelial neoplasia undergoing progestin therapy. In a retrospective study of 128 patients, we analyzed a total of 351 endometrial biopsy samples and categorized outcomes into responders (absence of residual disease) and nonresponders (presence of residual disease). We found aberrant biomarker expression in pretreatment cases: 48% for PTEN, 65% for PAX2, and 36% for β-catenin. Approximately 77.3% of patients responded to progestin treatment, with nonresponders showing significantly higher initial PTEN loss (75.86% vs 39.79%, P < 0.001). Nonresponders also demonstrated significant PTEN loss (53.33% vs 20.55%, P < 0.001), PAX2 loss (57.33% vs 41.22%, P < 0.05), and β-catenin nuclear staining (53.45% vs 27.91%, P < 0.01) in follow-up samples. In addition, nonresponders exhibited lower recovery of intact PTEN and PAX2, along with higher β-catenin aberrancy in cases initially showing normal β-catenin levels. We conclude that persistent aberrant PTEN and PAX2 expression, coupled with emerging aberrant β-catenin in follow-ups, indicates a greater likelihood of treatment failure. Conversely, the absence of these aberrations suggests successful progestin therapy. Our findings highlight the utility of this 3-marker panel in assessing residual disease status and predicting progestin treatment outcomes, thus offering critical insights for patient management.

Utility of a PAX2, PTEN, and β-catenin Panel in the Diagnosis of Atypical Hyperplasia/Endometrioid Intraepithelial Neoplasia in Endometrial Polyps.

The diagnosis of atypical hyperplasia/endometrioid intraepithelial neoplasm (AH/EIN) within endometrial polyps (EMPs) often poses a diagnostic conundrum. Our previous studies demonstrated that a panel of immunohistochemical (IHC) markers consisting of PAX2, PTEN, and β-catenin can be effectively utilized for the identification of AH/EIN. A total of 105 AH/EIN within EMP were analyzed using the 3-marker panel. We also evaluated these cases for the presence of morules. Benign EMP (n=90) and AH/EIN unassociated with polyp (n=111) served as controls. Aberrant expression of PAX2, PTEN, or β-catenin was observed in AH/EIN in EMP in 64.8%, 39.0%, and 61.9% of cases, respectively. At least 1 IHC marker was abnormal in 92.4% of cases. Overall, 60% of AH/EIN in EMP demonstrated abnormal results for≥2 IHC markers. The prevalence of PAX2 aberrancy was significantly lower in AH/EIN in EMP than in nonpolyp AH/EIN (64.8% vs. 81.1%, P =0.007), but higher than in benign EMP (64.8% vs. 14.4%, P <0.00001). The prevalence of β-catenin aberrancy was significantly higher in AH/EIN in EMP than in nonpolyp AH/EIN (61.9% vs. 47.7%, P =0.037). All control benign EMP demonstrated normal expression of PTEN and β-catenin. Morules were present in 38.1% of AH/EIN in EMP versus 24.3% in nonpolyp AH/EIN, and absent in benign EMP. A strong positive association was found between β-catenin and morules (Φ=0.64). Overall, 90% cases of atypical polypoid adenomyoma (n=6) and mucinous papillary proliferation (n=4) showed IHC marker aberrancy. In conclusion, the 3-marker IHC panel (PAX2, PTEN, and β-catenin) is (1) a useful tool in the diagnosis of AH/EIN in EMP; (2) PAX2 loss should be interpreted with caution and in combination with morphology and other markers.

β-catenin, Pax2, and Pten Panel Identifies Precancers Among Histologically Subdiagnostic Endometrial Lesions.

Despite refinements in histologic criteria for the diagnosis of endometrioid precancers, many challenging cases are encountered in daily practice, creating diagnostic uncertainty and suboptimal patient management. Recently, an immunohistochemical 3-marker panel consisting of β-catenin, Pax2, and Pten was identified as a useful diagnostic adjunct. However, previous studies focused either on cancers or diagnostically unambiguous precancers, leaving questions about the applicability and utility of the panel in endometria with architectural features near or below the threshold of accepted histologic criteria for endometrioid precancers. Here, in a retrospective study of 90 patients, we evaluated the performance of the 3-marker panel. Notably, the panel detected a subset of disordered proliferative endometria (8/44, 18%), nonatypical hyperplasias (19/40, 48%), and cases with ambiguous features (3/6, 50%) with aberrancy for ≥1 markers. Marker-aberrant cases were more likely to progress to endometrioid precancer or cancer (P=0.0002). Patterns of marker aberrancy in the index and progressor cases from individual patients provided evidence for origin in a common precursor, and next-generation sequencing of the progressor cases rationalized marker aberrancy for β-catenin and Pten. The results unequivocally demonstrate that some lesions that do not approach current histologic thresholds are bona fide neoplastic precursors with clinically-relevant driver events that can be detected by the 3-marker panel. The findings provide further validation for the diagnostic utility of the panel in clinical practice and its application in difficult or ambiguous cases.

New insights into extracellular and intracellular redox status in COVID-19 patients

BackgroundThe imbalance of redox homeostasis induces hyper-inflammation in viral infections. In this study, we explored the redox system signature in response to SARS-COV-2 infection and examined the status of these extracellular and intracellular signatures in COVID-19 patients. MethodThe multi-level network was constructed using multi-level data of oxidative stress-related biological processes, protein-protein interactions, transcription factors, and co-expression coefficients obtained from GSE164805, which included gene expression profiles of peripheral blood mononuclear cells (PBMCs) from COVID-19 patients and healthy controls. Top genes were designated based on the degree and closeness centralities. The expression of high-ranked genes was evaluated in PBMCs and nasopharyngeal (NP) samples of 30 COVID-19 patients and 30 healthy controls. The intracellular levels of GSH and ROS/O2• − and extracellular oxidative stress markers were assayed in PBMCs and plasma samples by flow cytometry and ELISA. ELISA results were applied to construct a classification model using logistic regression to differentiate COVID-19 patients from healthy controls. ResultsCAT, NFE2L2, SOD1, SOD2 and CYBB were 5 top genes in the network analysis. The expression of these genes and intracellular levels of ROS/O2• − were increased in PBMCs of COVID-19 patients while the GSH level decreased. The expression of high-ranked genes was lower in NP samples of COVID-19 patients compared to control group. The activity of extracellular enzymes CAT and SOD, and the total oxidant status (TOS) level were increased in plasma samples of COVID-19 patients. Also, the 2-marker panel of CAT and TOS and 3-marker panel showed the best performance. ConclusionSARS-COV-2 disrupts the redox equilibrium in immune cells and the upper respiratory tract, leading to exacerbated inflammation and increased replication and entrance of SARS-COV-2 into host cells. Furthermore, utilizing markers of oxidative stress as a complementary validation to discriminate COVID-19 from healthy controls, seems promising.

Performance of Serum β2-Microglobulin– and β-Trace Protein–Based Panel Markers and 2021 Creatinine- and Cystatin-Based GFR Estimating Equations in Pakistan

Performance of Serum β2-Microglobulin– and β-Trace Protein–Based Panel Markers and 2021 Creatinine- and Cystatin-Based GFR Estimating Equations in Pakistan

A New Panel-Estimated GFR, Including β2-Microglobulin and β-Trace Protein and Not Including Race, Developed in a Diverse Population

Glomerular filtration rate (GFR) estimation based on creatinine and cystatin C (eGFRcr-cys) is more accurate than estimated GFR (eGFR) based on creatinine or cystatin C alone (eGFRcr or eGFRcys, respectively), but the inclusion of creatinine in eGFRcr-cys requires specification of a person's race. β2-Microglobulin (B2M) and β-trace protein (BTP) are alternative filtration markers that appear to be less influenced by race than creatinine is. Study of diagnostic test accuracy. Development in a pooled population of 7 studies with 5,017 participants with and without chronic kidney disease. External validation in a pooled population of 7 other studies with 2,245 participants. Panel eGFR using B2M and BTP in addition to cystatin C (3-marker panel) or creatinine and cystatin C (4-marker panel) with and without age and sex or race. GFR measured as the urinary clearance of iothalamate, plasma clearance of iohexol, or plasma clearance of [51Cr]EDTA. Mean measured GFRs were 58.1 and 83.2 mL/min/1.73 m2, and the proportions of Black participants were 38.6% and 24.0%, in the development and validation populations, respectively. Indevelopment, addition of age and sex improved the performance of all equations compared with equations without age and sex, but addition of race did not further improve the performance. In validation, the 4-marker panels were more accurate than the 3-marker panels (P< 0.001). The 3-marker panel without race was more accurate than eGFRcys (percentage of estimates greater than 30% different from measured GFR [1 - P30] of 15.6% vs 17.4%; P= 0.01), and the 4-marker panel without race was as accurate as eGFRcr-cys (1 - P30 of 8.6% vs 9.4%; P= 0.2). Results were generally consistent across subgroups. No representation of participants with severe comorbid illness and from geographic areas outside of North America and Europe. The 4-marker panel eGFR is as accurate as eGFRcr-cys without requiring specification of race. A more accurate race-free eGFR could be an important advance.

Insulinoma-associated protein 1 is a robust nuclear immunostain for the diagnosis of small cell lung carcinoma in cytology smears.

In a significant percentage of patients with small cell lung carcinoma (SCLC), cytology samples represent the only source of tumor tissue. Ancillary immunocytochemistry (ICC) for neuroendocrine markers is an important adjunct for the diagnosis of SCLC. Insulinoma-associated protein 1 (INSM1) is a novel neuroendocrine marker proposed as an economical single-marker alternative to the traditional 3-marker panel of chromogranin, synaptophysin, and CD56. To the authors' knowledge, limited studies have evaluated INSM1 immunohistochemistry (IHC) for the diagnosis of SCLC and reported high sensitivities and specificities. The objective of the current study was to evaluate the sensitivity and specificity of INSM1 ICC on direct smears (DS) from patients with SCLC in comparison with IHC on small biopsies (SBs). All available DS and SBs from patients with SCLC who were diagnosed over the previous year were retrieved. Immunostaining for INSM1 was performed on alcohol-fixed DS and formalin-fixed SBs wherever available. A total of 10 DS and SBs from patients with non-small cell lung carcinoma were included for comparison. Nuclear staining for INSM1 in ≥1% tumor cells was interpreted as positive. Among a total of 60 patients with SCLC who were included in the current study, a total of 37 underwent INSM1 IHC on SBs and 36 underwent INSM1 ICC on DS. ICC was noninterpretable in 3 DS due to necrosis. The sensitivity of INSM1 IHC was 97% (36 of 37 cases) whereas the sensitivity of INSM1 ICC was 91% (30 of 33 cases) for the diagnosis of SCLC. Among matched IHC and ICC results available for 11 patients, 91% of cases (10 of 11 patients) demonstrated concordant IHC-ICC staining. All cases of non-small cell lung carcinoma were negative for INSM1 (100% specificity). INSM1 appears to be a robust and reliable ICC marker for the confirmation of SCLC diagnosis on cytology smears.

CD44, TGM2 and EpCAM as novel plasma markers in endometrial cancer diagnosis

BackgroundEndometrial cancer (EC) is the most common malignancy of the female reproductive tract. Despite years of research, the accurate screening strategy is still not available in this disease and it is usually diagnosed only after the clinical signs are present. The recent technological advances in analytical methodologies enabled detection of multiple molecules in one, small sample of biological materials. Such approach was undertaken in the presented study.MethodsConcentrations of aldehyde dehydrogenase 1 family, member A1 (ALDH1A1), carbonic anhydrase IX (CA9), CD44, epithelial cell adhesion molecule (EpCAM), hepsin, kallikrein-6, mesothelin, midkine, neural cell adhesion molecule L1 (L1CAM), and transglutaminase 2 (TGM2) were measured using MAGPIX®System in plasma samples of 45 EC, 20 healthy controls and 11 patients with endometriosis.ResultsSignificantly increased concentration in EC as compared to healthy controls were found in case of CD44 (p < 0.001), EpCAM (p = 0.033) and TGM2 (p < 0.001). EpCAM and mesothelin concentrations differed based on FIGO stages. Regression analysis revealed marker panels with high accuracy in detection of EC. The highest AUC 0.937 was attributed to the 3-marker panel of CD44/TGM2/EpCAM (84% sensitivity, 100% specificity), FIGO IA samples were discriminated from more advanced stages of EC with the mesothelin/grade 1 model featuring AUC of 0.911 (95.24% sensitivity, 78.26% specificity).ConclusionsNovel plasma biomarkers presenting good accuracy in diagnosing EC were found with TGM2 reported for the first time as plasma marker. It was also revealed that endometriosis may share similarities in the pattern of markers alterations characteristic for EC.

Combining urinary DNA methylation and cell-free microRNA biomarkers for improved monitoring of prostate cancer patients on active surveillance

PurposeProstate cancer (CaP) patients with low-grade tumors are enrolled in active surveillance (AS) programs and monitored with digital rectal exams (DREs), prostate-specific antigen (PSA) tests, and periodic invasive biopsies. Patients are “reclassified” with higher-risk disease if they show signs of disease progression. However, AS patients who will reclassify cannot be easily identified upfront and suffer morbidities associated with biopsy. Biomarkers derived from noninvasively obtained specimens such as serum or urine samples are promising alternatives to monitor patients with clinically insignificant cancer. Previously, we have characterized and validated a urinary DNA methylation panel and a serum miRNA panel for the prediction of patient reclassification in 2 independent AS cohorts. In this exploratory study, we have investigated cell-free miRNAs in the urinary supernatant combined with urinary DNA methylation markers to form an integrative panel for prediction of AS patient reclassification. MethodsPost-DRE urine was collected from 103 CaP patients on active surveillance. Urinary sediment DNA methylation levels of selected genes were previously analyzed using qPCR-based MethyLight assay. Using qRT-PCR, we analyzed the urinary supernatants for relative quantities of 10 miRNAs previously shown to be associated with AS reclassification. Logistic regression and Receiver Operating Characteristics curve analyses were performed to assess the predictive ability of miRNAs and DNA methylation biomarkers. ResultsWe identified a 3-marker panel, consisting of miR-24, miR-30c and CRIP3 methylation, that was significant for prediction of patient reclassification (Odds ratio = 2.166, 95% confidence interval = 1.22–3.847) with a negative predictive value of 90.9%. Our 3-marker panel also demonstrated additive value to PSA for prediction of patient reclassification (c-statistic = 0.717, ROC bootstrapped 1000 iteration P = 0.041). ConclusionA urinary integrated panel of methylation and miRNA markers is a promising approach to identify AS patients at risk for reclassification. Our 3-marker panel, with its high negative predictive value, would be beneficial to identify and preclude AS patients with truly indolent cancer and to personalize monitoring strategies for AS patients.

Detection of Gastric Cancer with Novel Methylated DNA Markers: Discovery, Tissue Validation, and Pilot Testing in Plasma.

Purpose: Gastric adenocarcinoma is the third most common cause of cancer mortality worldwide. Accurate and affordable noninvasive detection methods have potential value for screening and surveillance. Herein, we identify novel methylated DNA markers (MDM) for gastric adenocarcinoma, validate their discrimination for gastric adenocarcinoma in tissues from geographically separate cohorts, explore marker acquisition through the oncogenic cascade, and describe distributions of candidate MDMs in plasma from gastric adenocarcinoma cases and normal controls.Experimental Design: Following discovery by unbiased whole-methylome sequencing, candidate MDMs were validated by blinded methylation-specific PCR in archival case-control tissues from U.S. and South Korean patients. Top MDMs were then assayed by an analytically sensitive method (quantitative real-time allele-specific target and signal amplification) in a blinded pilot study on archival plasma from gastric adenocarcinoma cases and normal controls.Results: Whole-methylome discovery yielded novel and highly discriminant candidate MDMs. In tissue, a panel of candidate MDMs detected gastric adenocarcinoma in 92% to 100% of U.S. and South Korean cohorts at 100% specificity. Levels of most MDMs increased progressively from normal mucosa through metaplasia, adenoma, and gastric adenocarcinoma with variation in points of greatest marker acquisition. In plasma, a 3-marker panel (ELMO1, ZNF569, C13orf18) detected 86% (95% CI, 71-95) of gastric adenocarcinomas at 95% specificity.Conclusions: Novel MDMs appear to accurately discriminate gastric adenocarcinoma from normal controls in both tissue and plasma. The point of aberrant methylation during oncogenesis varies by MDM, which may have relevance to marker selection in clinical applications. Further exploration of these MDMs for gastric adenocarcinoma screening and surveillance is warranted. Clin Cancer Res; 24(22); 5724-34. ©2018 AACR.

Integrated analyses utilizing metabolomics and transcriptomics reveal perturbation of the polyamine pathway in oral cavity squamous cell carcinoma

Oral cavity squamous cell carcinoma (OSCC), the most common malignancy of the oral cavity, is associated with poor prognosis and high mortality worldwide. Moreover, knowledge of the metabolic alterations that occur in OSCC is still limited. In the present study, we used a quantitative metabolomic approach with chemical isotope labeling (CIL) to analyze alterations in the metabolite levels in paired cancerous (T) and adjacent noncancerous (AN) tissues from 31 OSCC patients. Using volcano plot and orthogonal projections to latent structure-discriminant analysis (OPLS-DA), we uncovered 99 dysregulated metabolites in OSCC and verified the identities of seven metabolites via comparison with authenticated standards. From these seven metabolites, we constructed a 3-marker panel, consisting of putrescine, glycyl-leucine, and phenylalanine, using a support vector machine (SVM) model that can discriminate T from AN with high sensitivity and specificity based on receiver operator characteristic (ROC) analysis. Furthermore, by integrating the metabolomics profiles with transcriptomics data obtained from the same sample set, we revealed the dysregulation of the polyamine pathway in OSCC. Our findings provide insights into the metabolic perturbations present in OSCC and have uncovered potential metabolic biomarkers and therapeutic targets for use in the treatment of OSCC.

Immunohistochemical Characterization of the Origins of Metastatic Well-differentiated Neuroendocrine Tumors to the Liver.

Metastatic neoplasms of unknown primary site pose a major challenge to patient management. As targeted therapies are now being tailored to neuroendocrine tumors (NETs) of different primary sites, identifying the origin of metastatic NETs has become increasingly important. Compared with more extensive efforts on metastatic adenocarcinomas of unknown primary, the literature on metastatic NETs (often to the liver) is relatively sparse and most studies are based on primary tumors. We sought to study metastatic well-differentiated NETs to the liver to identify markers that predict the site of origin. Eighty-five metastatic NETs to the liver were retrieved from the pathology archive. The primary sites were determined based on either pathologic review of the primary tumors (in most cases) or radiologic/clinical findings. Immunohistochemical labeling for TTF1, CDX2, ISL1, NKX2.2, and PDX1 was performed on either tissue microarrays or whole sections. The primary sites of the NETs in the study cohort included: pancreas (35%), small intestine (32%), rectum (8%), stomach (2%), bile duct (1%), lung (9%), and unknown primary (12%). We found predominant expression of TTF1 in lung carcinoid (63%), CDX2 in small intestinal (89%) and ISL1 in pancreatic NETs (77%), respectively. NKX2.2 was mainly expressed in NETs of the digestive organs. PDX1 was detected in a small percentage of pancreatic, small intestinal and the single bile duct NET. There was no statistically significant association between tumor grade (World Health Organization G1 vs. G2) and the expression of any of the above markers. The 3-marker panel (TTF1, CDX2, and ISL1) had sensitivities of 81%, 89%, and 63%, specificities of 100%, 94%, and 100%, positive predictive values of 100%, 89%, and 100%, and negative predictive values of 84%, 94%, and 96% in separating metastatic NETs into 3 major primary sites: pancreas/rectum, small intestine, and lung, respectively, with an overall accuracy of 82%. Furthermore, this panel predicted a primary site for 6 of the 10 NETs of unknown primary, which reduced the NETs of unknown primary from 12% to 5%. Thus, through immunohistochemical study of a large series of metastatic NETs to the liver, we have demonstrated the utility of a 3-marker panel for the identification of one or more potential primary sites of most metastatic NETs, which could provide practical guidance in patient management.

Glycans related to the CA19-9 antigen are elevated in distinct subsets of pancreatic cancers and improve diagnostic accuracy over CA19-9.

Background & AimsThe cancer antigen 19-9 (CA19-9) is the current best biomarker for pancreatic cancer, but it is not increased in approximately 25% of pancreatic cancer patients at a cut-off value that provides a 25% false-positive rate. We hypothesized that antigens related to the CA19-9 antigen, which is a glycan called sialyl-Lewis A (sLeA), are increased in distinct subsets of pancreatic cancers.MethodsWe profiled the levels of multiple glycans and mucin glycoforms in plasma from 200 subjects with either pancreatic cancer or benign pancreatic disease, and we validated selected findings in additional cohorts of 116 and 100 subjects, the latter run with the investigators blinded to diagnoses and including cancers that exclusively were early stage.ResultsWe found significant increases in 2 glycans: an isomer of sLeA called sialyl-Lewis X, present both in sulfated and nonsulfated forms, and the sialylated form of a marker for pluripotent stem cells, type 1 N-acetyl-lactosamine. The glycans performed as well as sLeA as individual markers and were increased in distinct groups of patients, resulting in a 3-marker panel that significantly improved upon any individual biomarker. The panel showed 85% sensitivity and 90% specificity in the combined discovery and validation cohorts, relative to 54% sensitivity and 86% specificity for sLeA; and it showed 80% sensitivity and 84% specificity in the independent test cohort, as opposed to 66% sensitivity and 72% specificity for sLeA.ConclusionsGlycans related to sLeA are increased in distinct subsets of pancreatic cancers and yield improved diagnostic accuracy compared with CA19-9.

Cross-species antibody microarray interrogation identifies a 3-protein panel of plasma biomarkers for early diagnosis of pancreas cancer.

Pancreatic ductal adenocarcinoma (PDA) is the fourth leading cause of cancer-related death in the United States, and its incidence is on the rise. Advanced disease is nearly uniformly lethal, emphasizing the need to identify PDA at its earliest stages. To discover early biomarkers of PDA, we evaluated the circulating proteome in murine preinvasive and invasive plasma samples and human prediagnostic and diagnostic samples. Using a customized antibody microarray platform containing >4,000 features, we interrogated plasma samples spanning preinvasive and invasive disease from a highly faithful mouse model of PDA. In parallel, we mined prediagnostic plasma from women in the Women's Health Initiative (WHI) who would later succumb to PDA together with matched, cancer-free control samples. Samples collected after an establishing diagnosis of PDA were also interrogated to further validate markers. We identified ERBB2 and TNC in our cross-species analyses, and multiple antibodies identified ESR1 in prediagnostic plasma from people that succumb to PDA. This 3-marker panel had an AUC of 0.86 (95% confidence interval [CI], 0.76-0.96) for the diagnostic cohort that increased to 0.97 (95% CI, 0.92-1.0) with CA19-9 included. The 3-marker panel also had an AUC of 0.68 (95% CI, 0.58-0.77) for the prediagnostic cohort. We identified potential disease detection markers in plasma up to 4 years before death from PDA with superior performance to CA19-9. These markers might be especially useful in high-risk cohorts to diagnose early, resectable disease, particularly in patients that do not produce CA19-9.

Pilot Application of Magnetic Nanoparticle-Based Biosensor for Necrotizing Enterocolitis.

Necrotizing Enterocolitis (NEC) is a major source of neonatal morbidity and mortality. There is an ongoing need for a sensitive diagnostic instrument to discriminate NEC from neonatal sepsis. We hypothesized that magnetic nanopartile-based biosensor analysis of gut injury-associated biomarkers would provide such an instrument. We designed a magnetic multiplexed biosensor platform, allowing the parallel plasma analysis of C-reactive protein (CRP), matrix metalloproteinase-7 (MMp7), and epithelial cell adhesion molecule (EpCAM). Neonatal subjects with sepsis (n=5) or NEC (n=10) were compared to control (n=5) subjects to perform a proof of concept pilot study for the diagnosis of NEC using our ultra-sensitive biosensor platform. Our multiplexed NEC magnetic nanoparticle-based biosensor platform was robust, ultrasensitive (Limit of detection LOD: CRP 0.6 pg/ml; MMp7 20 pg/ml; and EpCAM 20 pg/ml), and displayed no cross-reactivity among analyte reporting regents. To gauge the diagnostic performance, bootstrapping procedure (500 runs) was applied: MMp7 and EpCAM collectively differentiated infants with NEC from control infants with ROC AUC of 0.96, and infants with NEC from those with sepsis with ROC AUC of 1.00. The 3-marker panel comprising of EpCAM, MMp7 and CRP had a corresponding ROC AUC of 0.956 and 0.975, respectively. The exploration of the multiplexed nano-biosensor platform shows promise to deliver an ultrasensitive instrument for the diagnosis of NEC in the clinical setting.

A comprehensive immunohistochemistry algorithm for the histological subtyping of small biopsies obtained from non-small cell lung cancers.

Need for accurate histologic subtyping of non-small cell lung carcinomas (NSCLCs) is growing. IHC patterns may be ambiguous in some cases, rendering it difficult to determine subtypes. Tissue microarrays composed of 184 resected NSCLCs were stained for TTF-1, Napsin A, CK7, p40, p63, CK5/6, and mucicarmine. TTF-1 and Napsin A were chosen as the most accurate adenocarcinoma (ADC) marker (ACM), and p40 as squamous cell carcinoma (SCC) marker (SCM). We then prospectively performed IHC using these markers (TTF-1, Napsin A, and p40) in a cohort of small NSCLC biopsies (n=186) with ambiguous morphology. Of these biopsies, 82.8% (154/186) were classifiable into either ADC or SCC by applying '3-marker IHC panel'. Additional CK7, p63, and CK5/6 were applied in 30 biopsies with equivocal IHC patterns, including 18 ACM-/SCM- (double-negative) and 12 ACM+/SCM+ (double-positive) cases. Decision tree and support vector machine models revealed that TTF-1 was a critical single marker for ADC in double-positive cases (91.7% accuracy), whereas p63 and/or CK5/6 helped to subtype double-negative cases (72.2% accuracy). We propose a novel comprehensive algorithm for subtyping NSCLCs using a 3-marker IHC panel and additional p63 and CK5/6 that would be useful for subtyping small NSCLC biopsies.