Dataset Information

Enhancing prognosis prediction using pre-treatment nodal SUVmax and HPV status in cervical squamous cell carcinoma.

ABSTRACT:

Background

This study was to evaluate the prognostic value of metabolic parameters on F-18-FDG PET/CT and the status of human papillomavirus (HPV) infection and known prognostic variables for predicting tumor recurrence and investigating a prognostic model in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy (CCRT).

Methods

A total of 129 patients with cervical squamous cell carcinoma who underwent initial CCRT were eligible for this study. Univariate and multivariate analyses were performed using traditional prognostic factors, metabolic parameters, and HPV infection. Classification and regression decision tree (CART) was used to establish new classification.

Results

Among 129 patients, 29 patients (22.5%) had recurrence after a median follow-up of 60?months (range, 3-125?months). Tumor size, para-aortic lymph node metastasis, nodal SUVmax, and HPV infection status were identified as independent prognostic factors by multivariate analysis. The CART analysis classified the patients into three groups. The first node was nodal SUVmax, and HPV status was the second node for patients with nodal SUVmax ?7.49; Group A (nodal SUVmax ?7.49 and HPV positive, HR 1.0), Group B (nodal SUVmax ?7.49 and HPV negative, HR 3.56), and Group C (nodal SUVmax >?7.49, HR 10.13). Disease-free survival was significantly different among the three groups (p?ConclusionThe nodal SUVmax on F-18 FDG PET/CT and HPV infection status before CCRT are powerful independent prognostic factors for the prediction of disease-free survival in patients with cervical squamous cell carcinoma who underwent initial CCRT. We also suggest a simple prognosis prediction model using pre-treatment FDG PET/CT and HPV genotyping; however, it needs further validation in an independent dataset.

SUBMITTER: Hong CM

PROVIDER: S-EPMC6591806 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Importance:Clinical trials that deintensify treatment for patients with suspected human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC) use p16 expression to identify HPV-mediated tumors and guide treatment. While p16 staining has a strong correlation with good outcomes, approximately 12% of p16-positive patients have recurrent disease. Biomarkers that reveal tumor-specific characteristics, such as nodal involvement, may change therapy decisions. Objective:To assess whether if a tumor-specific genetic signature exists for node-negative vs node-positive HPV 16-positive/p16-positive OPSCCs. Design, Setting, and Participants:This was a retrospective cohort study with randomized case selection for p16 OPSCCs undertaken at a university-based, tertiary care cancer center. Samples were collected from patients with p16-positive OPSCC. A total of 21 HPV 16/p16-positive tumors were used in this study. Main Outcomes and Measures:Gene expression profiles of node-negative vs node-positive tumor samples were evaluated using a differential expression analysis approach and the sensitivity and specificity of a molecular signature was determined. Results:Among the 21 patients in the study (3 women, 18 men; mean [SD] age, 54.6 [9.6] years), 6 had node-negative disease and 15 had node-positive disease. Using differential expression analysis, we found 146 genes that were significantly different in patients with node-negative disease vs those with node-positive disease, of which 15 genes were used to create a genetic signature that could distinguish node-negative-like from node-positive-like disease. The resultant molecular signature has a sensitivity of 88.2% (95% CI, 63.6%-98.5%) and specificity of 85.7% (95% CI, 42.1%-99.6%). The positive likelihood ratio of this signature was 6.1 (95% CI, 1.0-38.2) and the negative likelihood ratio was 0.1 (95% CI, 0.04-0.5). Given this population's prevalence of node-positive disease of 70.8%, the positive- and negative-predicative values for this gene signature were 93.7% (95% CI, 70.8%-98.9%) and 75.0% (95% CI, 44.1%-92.0%), respectively. In addition, we developed a gene signature using agnostic, machine learning software that identified a 40-gene profile that predicts node-negative disease from node-positive disease (area under the curve, 0.93; 95% CI, 0.63-1.00). Conclusions and Relevance:Many HPV-16 and p16-positive tumors are treated as "lower-risk," but they do not have similar genetic compositions at the biological level. The identification of subgroups with unique expression patterns, such as those with nodal metastases, may guide physicians toward alternative or more aggressive therapies. In our study, unguided clustering suggested that that the larger biological characteristics of a tumor could be a better prognostic biomarker.

Project description:PurposeThere is a lack of biomarkers for accurately prognosticating outcome in both human papillomavirus-related (HPV+) and tobacco- and alcohol-related (HPV-) oropharyngeal squamous cell carcinoma (OPSCC). The aims of this study were to i) develop and evaluate radiomic features within (intratumoral) and around tumor (peritumoral) on CT scans to predict HPV status; ii) investigate the prognostic value of the radiomic features for both HPV- and HPV+ patients, including within individual AJCC eighth edition-defined stage groups; and iii) develop and evaluate a clinicopathologic imaging nomogram involving radiomic, clinical, and pathologic factors for disease-free survival (DFS) prediction for HPV+ patients.Experimental designThis retrospective study included 582 OPSCC patients, of which 462 were obtained from The Cancer Imaging Archive (TCIA) with available tumor segmentation and 120 were from Cleveland Clinic Foundation (CCF, denoted as SCCF) with HPV+ OPSCC. We subdivided the TCIA cohort into training (ST, 180 patients) and validation (SV, 282 patients) based on an approximately 3:5 ratio for HPV status prediction. The top 15 radiomic features that were associated with HPV status were selected by the minimum redundancy-maximum relevance (MRMR) using ST and evaluated on SV. Using 3 of these 15 top HPV status-associated features, we created radiomic risk scores for both HPV+ (RRSHPV+) and HPV- patients (RRSHPV-) through a Cox regression model to predict DFS. RRSHPV+ was further externally validated on SCCF. Nomograms for the HPV+ population (Mp+RRS) were constructed. Both RRSHPV+ and Mp+RRS were used to prognosticate DFS for the AJCC eighth edition-defined stage I, stage II, and stage III patients separately.ResultsRRSHPV+ was prognostic for DFS for i) the whole HPV+ population [hazard ratio (HR) = 1.97, 95% confidence interval (CI): 1.35-2.88, p < 0.001], ii) the AJCC eighth stage I population (HR = 1.99, 95% CI: 1.04-3.83, p = 0.039), and iii) the AJCC eighth stage II population (HR = 3.61, 95% CI: 1.71-7.62, p < 0.001). HPV+ nomogram Mp+RRS (C-index, 0.59; 95% CI: 0.54-0.65) was also prognostic of DFS (HR = 1.86, 95% CI: 1.27-2.71, p = 0.001).ConclusionCT-based radiomic signatures are associated with both HPV status and DFS in OPSCC patients. With additional validation, the radiomic signature and its corresponding nomogram could potentially be used for identifying HPV+ OPSCC patients who might be candidates for therapy deintensification.

Project description:The present study was conducted to investigate the possible prognostic value of molecular markers LRIG1‑2 and LIM domain 7 protein (LMO7) in vulvar squamous cell carcinoma (VSCC) and their possible correlation to human papilloma virus (HPV)‑ and p16INK4a‑status of the tumors. Patients diagnosed with VSCC at the University Hospital of Umeå, Sweden, during the years 1990‑2013 were selected. Tumor blocks were retrieved from tissue archives and clinical data were collected from the records of patients. HPV‑PCR analysis, HPV genotyping and immunohistochemistry were performed. In total, 112 patients were included. Forty percent of the tumors were HPV‑positive, 27% were p16INK4a‑positive and 23% were positive for both HPV and p16INK4a (considered HPV‑driven). HPV‑positivity and p16INK4a‑positivity were associated with prolonged disease‑free survival (DFS) in Kaplan‑Meier survival analysis. Leucine‑rich repeats and immunoglobulin‑like domains 1 (LRIG1) immunoreactivity was not significantly associated with survival. High leucine‑rich repeats and immunoglobulin‑like domains 2 (LRIG2) immunoreactivity was associated with a prolonged overall survival (OS) (P=0.001). By analyzing HPV‑negative cases only, it was determined that high LRIG2 immunoreactivity was associated with both favorable OS (P=0.008) and DFS (P=0.031). LRIG2 immunoreactivity was also an independent prognostic factor in multivariate analysis of OS (P=0.002, HR=0.41; 95% CI, 0.24‑0.71). High immunoreactivity with LMO7‑1250 antibody was associated with survival benefits in the whole cohort (OS; P=0.011) although DFS was only prolonged in HPV‑negative and not HPV‑driven tumors (P=0.038 and 0.042, respectively). The present study indicated that LRIG2 and LMO7 may be useful prognostic markers in VSCC, particularly for patients without HPV‑driven tumors or with advanced tumors at diagnosis. In contrast to earlier observations regarding other types of squamous cell carcinoma, LRIG1 was not a significant prognostic factor in VSCC.