Whole-body total lesion glycolysis is an independent predictor in patients with esophageal cancer treated with definitive chemoradiotherapy

Development of a prediction model for head and neck volume reduction by clinical factors, dose-volume histogram parameters and radiomics in head and neck cancer†

In external radiotherapy of head and neck (HN) cancers, the reduction of irradiation accuracy due to HN volume reduction often causes a problem. Adaptive radiotherapy (ART) can effectively solve this problem; however, its application to all cases is impractical because of cost and time. Therefore, finding priority cases is essential. This study aimed to predict patients with HN cancers are more likely to need ART based on a quantitative measure of large HN volume reduction and evaluate model accuracy. The study included 172 cases of patients with HN cancer who received external irradiation. The HN volume was calculated using cone-beam computed tomography (CT) for irradiation-guided radiotherapy for all treatment fractions and classified into two groups: cases with a large reduction in the HN volume and cases without a large reduction. Radiomic features were extracted from the primary gross tumor volume (GTV) and nodal GTV of the planning CT. To develop the prediction model, four feature selection methods and two machine-learning algorithms were tested. Predictive performance was evaluated by the area under the curve (AUC), accuracy, sensitivity and specificity. Predictive performance was the highest for the random forest, with an AUC of 0.662. Furthermore, its accuracy, sensitivity and specificity were 0.692, 0.700 and 0.813, respectively. Selected features included radiomic features of the primary GTV, human papillomavirus in oropharyngeal cancer and the implementation of chemotherapy; thus, these features might be related to HN volume change. Our model suggested the potential to predict ART requirements based on HN volume reduction .

Risk stratification of oesophageal squamous cell carcinoma using change in total lesion glycolysis and number of PET-positive lymph nodes

BACKGROUND

The efficacy of neoadjuvant chemotherapy (NACT) correlates with patient survival in oesophageal squamous cell carcinoma (OSCC), but optimal evaluation of the treatment response based on PET-CT parameters has not been established.

METHODS

We analysed 226 OSCC patients who underwent PET-CT before and after NACT followed by surgery. We assessed SUVmax, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) for the primary tumour and the number of PET-positive lymph nodes before and after NACT to predict patient survival.

RESULTS

In a stepwise analysis, we defined 60%, 80%, and 80% as the optimal cut-off values for SUVmax, MTV, and TLG reduction, respectively, to distinguish responders and non-responders to NACT. In the ROC analysis, the TLG reduction rate was the best predictor of recurrence among PET-CT parameters. The TLG responders achieved significantly more favourable prognoses than non-responders (2-year progression-free survival [PFS] rate: 64.1% vs. 38.5%; P = 0.0001). TLG reduction rate (HR 2.58; 95% CI 1.16-5.73) and the number of PET-positive lymph nodes after NACT (HR 1.79; 95% CI 1.04-3.08) were significant independent prognostic factors.

CONCLUSIONS

TLG reduction is the best predictor of prognosis. Preoperative PET-CT evaluation of both the primary tumour and lymph nodes could accurately stratify risk in OSCC patients.

18F-Fluorodeoxyglucose Positron Emission Tomography Parameters can Predict Long-Term Outcome Following Trimodality Treatment for Oesophageal Cancer

AIMS

¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸FDG-PET/CT) is routinely used for the pre-treatment staging of oesophageal or gastro-oesophageal junction cancers (EGEJC). The aim of this study was to identify objective ¹⁸FDG-PET/CT-derived parameters that can aid in predicting the patterns of recurrence and prognostication in patients with EGEJC.

PATIENTS AND METHODS

EGEJC patients referred for consideration of preoperative chemoradiation therapy were identified and clinicopathological data were collected. ¹⁸FDG-PET/CT imaging data were reviewed and correlated with treatment outcomes. Maximum standardised uptake value (SUV_max), metabolic tumour volume (MTV) and total lesion glycolysis were assessed and association with recurrence-free survival (RFS), locoregional recurrence-free survival (LR-RFS), oesophageal cancer-specific survival (ECSS) and overall survival were evaluated using receiver operating characteristic curves, as well as Cox regression and Kaplan-Meier models.

RESULTS

In total, 191 EGEJC patients completed trimodality treatment and 164 with ¹⁸FDG-PET/CT data were included in this analysis. At the time of analysis, 15 (9.1%), 70 (42.7%) and two (1.2%) patients were noted to have locoregional, distant and both locoregional and distant metastases, respectively. The median RFS was 30 months (9.6-50.4) and the 5-year RFS was 31.1%. The 5-year overall survival and ECSS were both noted to be 34.8%. Pre-treatment MTV₂₅ > 28.5 cm³ (P = 0.029), MTV₄₀ > 12.4 cm³ (P = 0.018) and MTV₅₀ > 10.2 cm³ (P = 0.005) predicted for worse LR-RFS, ECSS and overall survival for MTV definition of voxels ≥25%, 40% and 50% of SUV_max.

CONCLUSION

¹⁸FDG-PET/CT parameters MTV and total lesion glycolysis are useful prognostic tools to predict for LR-RFS, ECSS and overall survival in EGEJC. MTV had the highest accuracy in predicting clinical outcomes. The volume cut-off points we identified for different MTV thresholds predicted outcomes with significant accuracy and may potentially be used for decision making in clinical practice.

Prognostic value of baseline 18F-FDG PET/CT in patients with esophageal squamous cell carcinoma treated with definitive (chemo)radiotherapy

PURPOSE

To investigate the prognostic value of baseline ¹⁸F-FDG PET/CT in patients with esophageal squamous cell carcinoma (ESCC) treated with definitive (chemo)radiotherapy.

METHODS

A total of 98 ESCC patients with cTNM stage T1-4, N1-3, M0 who received definitive (chemo)radiotherapy after ¹⁸F-FDG PET/CT examination from December 2013 to December 2020 were retrospectively analyzed. Clinical factors included age, sex, histologic differentiation grade, tumor location, clinical stage, and treatment strategies. Parameters obtained by ¹⁸F-FDG PET/CT included SUV_max of primary tumor (SUV_Tumor), metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUV_max of lymph node (SUV_LN), PET positive lymph nodes (PLNS) number, the shortest distance between the farthest PET positive lymph node and the primary tumor in three-dimensional space after the standardization of the patient BSA (SD_max(LN-T)). Univariate and multivariate analysis was conducted by Cox proportional hazard model to explore the significant factors affecting overall survival (OS) and progression-free survival (PFS) in ESCC patients.

RESULTS

Univariate analysis showed that tumor location, SUV_Tumor, MTV, TLG, PLNS number, SD_{max (LN-T)} were significant predictors of OS and tumor location, and clinical T stage, SUV_Tumor, MTV, TLG, SD_{max (LN-T)} were significant predictors of PFS (all p < 0.1). Multivariate analysis showed that MTV and SD_{max (LN-T)} were independent prognostic factors for OS (HR = 1.018, 95% CI 1.006-1.031; p = 0.005; HR = 6.988, 95% CI 2.119-23.042; p = 0.001) and PFS (HR = 1.019, 95% CI 1.005-1.034; p = 0.009; HR = 5.819, 95% CI 1.921-17.628; p = 0.002). Combined with independent prognostic factors MTV and SD_{max (LN-T)}, we can further stratify patient risk.

CONCLUSIONS

Before treatment, ¹⁸F-FDG PET/CT has important prognostic value for patients with ESCC treated with definitive (chemo)radiotherapy. The lower the value of MTV and SD_{max (LN-T)}, the better the prognosis of patients.

Development and validation of an [18F]FDG-PET/CT radiomic model for predicting progression-free survival for patients with stage II - III thoracic esophageal squamous cell carcinoma who are treated with definitive chemoradiotherapy

BACKGROUND

Radiomics is a method for extracting a large amount of information from images and used to predict treatment outcomes, side effects and diagnosis. In this study, we developed and validated a radiomic model of [¹⁸F]FDG-PET/CT for predicting progression-free survival (PFS) of definitive chemoradiotherapy (dCRT) for patients with esophageal cancer.

MATERIAL AND METHODS

Patients with stage II - III esophageal cancer who underwent [¹⁸F]FDG-PET/CT within 45 days before dCRT between 2005 and 2017 were included. Patients were randomly assigned to a training set (85 patients) and a validation set (45 patients). Radiomic parameters inside the area of standard uptake value ≥ 3 were calculated. The open-source software 3D slicer and Pyradiomics were used for segmentation and calculating radiomic parameters, respectively. Eight hundred sixty radiomic parameters and general information were investigated.In the training set, a radiomic model for PFS was made from the LASSO Cox regression model and Rad-score was calculated. In the validation set, the model was applied to Kaplan-Meier curves. The median value of Rad-score in the training set was used as a cutoff value in the validation set. JMP was used for statistical analysis. RStudio was used for the LASSO Cox regression model. p < 0.05 was defined as significant.

RESULTS

The median follow-up periods were 21.9 months for all patients and 63.4 months for survivors. The 5-year PFS rate was 24.0%. In the training set, the LASSO Cox regression model selects 6 parameters and made a model. The low Rad-score group had significantly better PFS than that the high Rad-score group (p = 0.019). In the validation set, the low Rad-score group had significantly better PFS than that the high Rad-score group (p = 0.040).

CONCLUSIONS

The [¹⁸F]FDG-PET/CT radiomic model could predict PFS for patients with esophageal cancer who received dCRT.

Prognostic value of fibroblast activation protein expressing tumor volume calculated from [68 Ga]Ga-FAPI PET/CT in patients with esophageal squamous cell carcinoma

BACKGROUND

This study aimed to investigate the prognostic value of semiquantitative parameters derived from [68 Ga]Ga-fibroblast activation protein inhibitor (FAPI) PET/CT for patients with esophageal squamous cell carcinoma (ESCC) treated with definitive chemoradiotherapy.

METHODS

We conducted a retrospective analysis on patients from a prospective parent study (NCT04416165). A total of 45 patients with locally advanced ESCC who underwent [68 Ga]Ga-FAPI from December 2019 to March 2021 were included. The maximum standard uptake value (SUVmax), gross tumor volume (GTV), and total lesion-FAPI (TL-FAPI) of the primary tumor were calculated from the corresponding PET/CT image. Unpaired parameters were compared using Student's t test or the Mann-Whitney U test. Paired parameters were compared using the paired t test or the Wilcoxon matched-pairs signed-rank test. Kaplan-Meier curves were generated to calculate progression-free survival (PFS) and overall survival (OS) rates, and Cox regression analysis was performed to determine which PET/CT parameters were prognostic factors for PFS and/or OS.

RESULTS

Thirty-four of the 45 patients met the criteria, and the median follow-up time was 24 months (16-29 months). SUVmax-FAPI, GTVFAPI, and TL-FAPI in patients with stage T4 tumors were significantly higher than those in patients with stage T2/T3 tumors (all P < 0.01). In the univariate Cox regression analysis, T stage, N stage, GTVFAPI, and TL-FAPI were associated with PFS, and T stage, GTVFAPI, and TL-FAPI were associated with OS. Upon multivariable analysis, GTVFAPI was an independent prognostic factor for both PFS (hazard ratio (HR), 5.76; 95% confidence interval (CI), 2.13-15.57, P = 0.001) and OS (HR, 4.96; 95% CI, 2.55-18.79, P = 0.001).

CONCLUSION

This pilot study revealed that [68 Ga]Ga-FAPI PET/CT may have prognostic value for patients with ESCC treated with definitive chemoradiotherapy. It may aid in personalized patient management by steering treatment modifications before therapy. Prospective studies with larger samples and longer observation periods are needed.

Glycolytic Genes Predict Immune Status and Prognosis Non-Small-Cell Lung Cancer Patients with Radiotherapy and Chemotherapy

Background

Non-small-cell lung cancer (NSCLC) is a major health problem that endangers human health. The prognosis of radiotherapy or chemotherapy is still unsatisfactory. This study is aimed at investigating the predictive value of glycolysis-related genes (GRGs) on the prognosis of NSCLC patients with radiotherapy or chemotherapy.

Methods

Download the clinical information and RNA data of NSCLC patients receiving radiotherapy or chemotherapy from TCGA and geo databases and obtain GRGs from MsigDB. The two clusters were identified by consistent cluster analysis, the potential mechanism was explored by KEGG and GO enrichment analyses, and the immune status was evaluated by estimate, TIMER, and quanTIseq algorithms. Lasso algorithm is used to build the corresponding prognostic risk model.

Results

Two clusters with different GRG expression were identified. The high-expression subgroup had poor overall survival. The results of KEGG and GO enrichment analyses suggest that the differential genes of the two clusters are mainly reflected in metabolic and immune-related pathways. The risk model constructed with GRGs can effectively predict the prognosis. The nomogram combined with the model and clinical characteristics has good clinical application potential.

Conclusion

In this study, we found that GRGs are associated with tumor immune status and can assess the prognosis of NSCLC patients receiving radiotherapy or chemotherapy.

The usefulness of the total metabolic tumor volume for predicting the postoperative recurrence of thoracic esophageal squamous cell carcinoma

Background

Induction or adjuvant therapies are not always beneficial for thoracic esophageal squamous cell carcinoma (ESCC) patients, and it is thus important to identify patients at high risk for postoperative ESCC recurrence. We investigated the usefulness of the total metabolic tumor volume (TMTV) for predicting the postoperative recurrence of thoracic ESCC.

Methods

We retrospectively analyzed the cases of 163 thoracic ESCC patients (135 men, 28 women; median age of 66 [range 34–82] years) treated at our hospital in 2007–2012. The TMTV was calculated from the fluorine-18 fluorodeoxyglucose (18F-FDG) uptake in the primary lesion and lymph node metastases. The optimal cut-off values for relapse and non-relapse were obtained by the time-dependent receiver operating curve analyses. Relapse-free survival (RFS) was evaluated by the Kaplan-Meier method, and between-subgroup differences in survival were analyzed by log-rank test. The prognostic significance of metabolic parameters and clinicopathological variables was assessed by a Cox proportional hazard regression analysis. The difference in the failure patterns after surgical resection was evaluated using the χ2-test.

Results

The optimal cut-off value of TMTV for discriminating relapse from non-relapse was 3.82. The patients with a TMTV ≥3.82 showed significantly worse prognoses than those with low values (p < 0.001). The TMTV was significantly related to RFS (model 1 for preoperative risk factors: TMTV: hazard ratio [HR] =2.574, p = 0.004; model 2 for preoperative and postoperative risk factors: HR = 1.989, p = 0.044). The combination of the TMTV and cN0–1 or pN0–1 stage significantly stratified the patients into low-and high-risk recurrence groups (TMTV cN0–1, p < 0.001; TMTV pN0–1, p = 0.004). The rates of hematogenous and regional lymph node metastasis were significantly higher in the patients with TMTV ≥3.82 than those with low values (hematogenous metastasis, p < 0.001, regional lymph node metastasis, p = 0.011).

Conclusions

The TMTV was a more significantly independent prognostic factor for RFS than any other PET parameter in patients with resectable thoracic ESCC. The TMTV may be useful for the identifying thoracic ESCC patients at high risk for postoperative recurrence and for deciding the patient management.

Volumetric Evaluation of Staging 18F-FDG PET/CT Images in Patients with Esophageal Cancer

Objectives

The aim of this study was to evaluate the metastatic potential of primary tumor and survival in esophageal cancer (EC) patients by using metabolic tumor volume (MTV) and total lesion glycolysis (TLG) from the staging 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) images. Another aim is to determine a tumor volume-based cut-off value to predict long-term survival.

Methods

Medical records of EC patients were retrospectively evaluated. Sixty-two patients with staging 18F-FDG PET/CT and at least five years of follow-up were included in the study. The region of interest to the primary tumor and all metastatic sites was created and MTV and TLG values of the primary tumor (MTVp, TLGp) and total tumor volume (MTVt and TLGt) values were obtained. The relationship between the obtained MTV and TLG values and short-time (one-year) and long time (five-year) survival was investigated.

Results

Significant factors on survival were determined as lymph node or distant metastasis (p=0.024, 0.008, respectively) at the staging PET/CT. A significant relationship between volumetric parameters of the primary tumor and total tumor burden (MTVp, TLGp, MTVwb and TLGwb) between survivors and non-survivors for one-year and five-year was detected. In receiver operating characteristics analysis, the most significant volumetric parameter was MTVwb, with area under curve 0.771 in estimated five-year survival. The best cut-off value was detected as 36.1 mL with 78% sensitivity and 75% specificity for MTVwb in determining long-term survivors.

Conclusion

Tumor burden in 18F-FDG PET/CT images at the time of staging of patients with EC will contribute to the prediction of long-term survivors.

FDG-PET/CT imaging parameters for predicting spontaneous regression of methotrexate-associated lymphoproliferative disorder in patients with rheumatoid arthritis

In this study, we investigated the usefulness of FDG-PET/CT for predicting spontaneous regression in methotrexate-associated lymphoproliferative disorder (MTX-LPD). Twenty patients with rheumatoid arthritis who were diagnosed with MTX-LPD were enrolled in the study. These patients were divided into those who showed spontaneous regression (SR group: ten patients) and those who received chemotherapy after discontinuation of MTX (CTx group: ten patients). Between-group differences in potential biomarkers were compared, including clinical markers at the onset of LPD [serum LDH and interleukin 2 receptor (sIL-2R)], change in absolute number of peripheral lymphocytes (ΔALC) over follow-up, and the FDG-PET/CT-derived parameters of maximum standardized uptake value (SUVmax), mean SUV (SUVmean), peak SUV (SUVpeak), sum of the metabolic tumor volume (MTVsum), and sum of total lesion glycolysis (TLGsum). The levels of sIL-2R, MTVsum, and TLGsum were significantly lower in the SR group than in the CTx group. In addition, ΔALC was higher in the SR group. In conclusion, MTV and TLG values measured by FDG-PET/CT may be suitable for use as predictors of SR in patients with MTX-LPD.

A deep learning-based radiomics approach to predict head and neck tumor regression for adaptive radiotherapy

Early regression—the regression in tumor volume during the initial phase of radiotherapy (approximately 2 weeks after treatment initiation)—is a common occurrence during radiotherapy. This rapid radiation-induced tumor regression may alter target coordinates, necessitating adaptive radiotherapy (ART). We developed a deep learning-based radiomics (DLR) approach to predict early head and neck tumor regression and thereby facilitate ART. Primary gross tumor volume (GTVp) was monitored in 96 patients and nodal GTV (GTVn) in 79 patients during treatment. All patients underwent two computed tomography (CT) scans: one before the start of radiotherapy for initial planning and one during radiotherapy for boost planning. Patients were assigned to regression and nonregression groups according to their median tumor regression rate (ΔGTV/treatment day from initial to boost CT scan). We input a GTV image into the convolutional neural network model, which was pretrained using natural image datasets, via transfer learning. The deep features were extracted from the last fully connected layer. To clarify the prognostic power of the deep features, machine learning models were trained. The models then predicted the regression and nonregression of GTVp and GTVn and evaluated the predictive performance by 0.632 + bootstrap area under the curve (AUC). Predictive performance for GTVp regression was highest using the InceptionResNetv2 model (mean AUC = 0.75) and that for GTVn was highest using NASNetLarge (mean AUC = 0.73). Both models outperformed the handcrafted radiomics features (mean AUC = 0.63 for GTVp and 0.61 for GTVn) or clinical factors (0.64 and 0.67, respectively). DLR may facilitate ART for improved radiation side-effects and target coverage.

Pretreatment 18F-FDG PET/CT-Derived Parameters in Predicting Clinical Outcomes of Locally Advanced Upper Third Esophageal Squamous Cell Carcinoma After Definitive Chemoradiation Therapy

Purpose

The aim of this study was to investigate whether standard uptake values (SUVs) of pretreatment ¹⁸F-FDG PET/CT were the surrogate parameters for predicting the outcomes in locally advanced esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy.

Materials and Methods

Sixty patients with esophageal squamous cell carcinoma underwent pretreatment ¹⁸F-FDG PET/CT and received definitive chemoradiotherapy. ¹⁸F-FDG metabolic parameters including SUVmax, SUVmean, SULpeak, total lesion glycolysis (TLG), and metabolic tumor volume (MTV) of primary tumor were calculated. The receiver-operating characteristic (ROC) curve was used to determine the optimal cutoff value of FDG PET/CT-derived parameters that associated with treatment response. Estimating progression-free survival (PFS) and overall survival (OS) was analyzed by using Kaplan-Meier methods. Univariate and multivariate analysis for PFS and OS was performed using Cox regression.

Results

Complete response was achieved in 38.3%. The 4-year OS and PFS rates were 48.6% and 44.4%, respectively. SUVmean with a cutoff value of 6.1 could predict complete response with sensitivity of 69.6%, specificity of 78.4%, and accuracy of 75%. Cox multi-factor regression analyses revealed SUVmean > 6.1 as an independent prognostic factor for OS (HR = 6.74, p = 0.02) and PFS (HR = 6.53, p < 0.001).

Conclusions

Our study suggests that SUVmean of the primary tumor in pretreatment ¹⁸F-FDG PET/CT may be used as an independent predictor in esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy.

18F-FDG PET/CT Parameters for Predicting Prognosis in Esophageal Cancer Patients Treated With Concurrent Chemoradiotherapy

Background and Aims:

This study evaluated the prognostic value of ¹⁸F-fluorodeoxyglucose positron emission tomography with integrated computed tomography (¹⁸F-FDG PET/CT) performed before and after concurrent chemoradiotherapy (CCRT) in esophageal cancer.

Methods:

We analyzed the prognosis of 50 non-metastatic squamous cell esophageal cancer (T1-4N0-2) patients who underwent CCRT with curative intent at Inje University Busan Paik Hospital and Haeundae Paik Hospital from 2009 to 2019. Median total radiation dose was 54 Gy (range 34-66 Gy). Our aim was to investigate the relationship between PET/CT values and prognosis. The primary end point was progression-free survival (PFS).

Results:

The median follow-up period was 9.9 months (range 1.7-85.7). Median baseline maximum standard uptake value (SUVmax) was 14.2 (range 3.2-27.7). After treatment, 29 patients (58%) showed disease progression. The 3-year PFS and overall survival (OS) were 24.2% and 54.5%, respectively. PFS was significantly lower (P = 0.015) when SUVmax of initial PET/CT exceeded 10 (n = 22). However, OS did not reach a significant difference based on maximum SUV (P = 0.282). Small metabolic tumor volume (≤14.1) was related with good PFS (P = 0.002) and OS (P = 0.001). Small total lesion of glycolysis (≤107.3) also had a significant good prognostic effect on PFS (P = 0.009) and OS (P = 0.025). In a subgroup analysis of 18 patients with follow-up PET/CT, the patients with SUV max ≤3.5 in follow-up PET/CT showed longer PFS (P = 0.028) than those with a maximum SUV >3.5.

Conclusion:

Maximum SUV of PET/CT is useful in predicting prognosis of esophageal cancer patients treated with CCRT. Efforts to find more effective treatments for patients at high risk of progression are still warranted.

Alteration of plasma metabolites associated with chemoradiosensitivity in esophageal squamous cell carcinoma via untargeted metabolomics approach

BACKGROUND

To investigate the differences in plasma metabolomic characteristics between pathological complete response (pCR) and non-pCR patients and identify biomarker candidates for predicting the response to neoadjuvant chemoradiotherapy (nCRT) in esophageal squamous cell carcinoma (ESCC).

METHODS

A total of 46 ESCC patients were included in this study. Gas chromatography time-of- flight mass spectrometry (GC-TOF/MS) technology was applied to detect the plasma samples collected before nCRT via untargeted metabolomics analysis.

RESULTS

Five differentially expressed metabolites (out of 109) was found in plasma between pCR and non-pCR groups. Compared with non-pCR group, isocitric acid (p = 0.0129), linoleic acid (p = 0.0137), citric acid (p = 0.0473) were upregulated, while L-histidine (p = 0.0155), 3'4 dihydroxyhydrocinnamic acid (p = 0.0339) were downregulated in the pCR plasma samples. Pathway analyses unveiled that citrate cycle (TCA cycle), glyoxylate and dicarboxylate metabolic pathway were associated with ESCC chemoradiosensitivity.

CONCLUSION

The present study provided supporting evidence that GC-TOF/MS based metabolomics approach allowed identification of metabolite differences between pCR and non-pCR patients in plasma levels, and the systemic metabolic status of patients may reflect the response of ESCC patient to neoadjuvant chemoradiotherapy.

Prognostic value of lymph node to primary tumor standardized uptake value ratio in unresectable esophageal cancer

Background

Unresectable esophageal cancer harbors high mortality despite chemoradiotherapy. Better patient selection for more personalized management may result in better treatment outcomes. We presume the ratio of maximum standardized uptake value (SUV) of metastatic lymph nodes to primary tumor (NTR) in 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (FDG PET/CT) may provide prognostic information and further stratification of these patients.

Methods

The patients with non-metastatic and unresectable esophageal squamous cell carcinoma (SCC) receiving FDG PET/CT staging and treated by chemoradiotherapy were retrospectively reviewed. Receiver operating characteristic (ROC) analysis was performed to determine the optimal cut-off value for NTR. Kaplan-Meier method and Cox regression model were used for survival analyses and multivariable analyses, respectively.

Results

From 2010 to 2016, 96 eligible patients were analyzed. The median follow-up time was 10.2 months (range 1.6 to 83.6 months). Using ROC analysis, the best NTR cut-off value was 0.46 for prediction of distant metastasis. The median distant metastasis-free survival (DMFS) was significantly lower in the high-NTR group (9.5 vs. 22.2 months, p = 0.002) and median overall survival (OS) (9.5 vs. 11.6 months, p = 0.013) was also significantly worse. Multivariable analysis revealed that NTR was an independent prognostic factor for DMFS (hazard ratio [HR] 1.81, p = 0.023) and OS (HR 1.77, p = 0.014).

Conclusions

High pretreatment NTR predicts worse treatment outcomes and could be an easy-to-use and helpful prognostic factor to provide more personalized treatment for patients with non-metastatic and unresectable esophageal SCC.

CREPT is a novel predictor of the response to adjuvant therapy or concurrent chemoradiotherapy in esophageal squamous cell carcinoma

CREPT has been shown to be highly expressed in most tumors and is associated with a poor prognosis, but the histologic characteristics of CREPT expression and its impact on clinical outcomes in esophageal squamous cell carcinoma (ESCC) are unclear. Therefore, we retroactively evaluated tissue microarrays (TMA) from 300 surgical cases, including 300 ESCC tissues and 161 adjacent non-tumor tissues, and pretreatment tumor biopsies from 113 concurrent chemoradiotherapy (CCRT) cases by immunohistochemistry (IHC). Notably, CREPT was increasingly expressed from non-cancerous tissues to atypical hyperplasia to tumor tissues (P < 0.01). Furthermore, patients were divided into low CREPT (≤ 8 scores) and high CREPT (> 8 scores) groups. Patients with high CREPT expressions had a worse overall survival (OS) (5-year OS: 40.9% vs. 50.1%, P=0.040) and disease-free survival (DFS) (5-year DFS: 29.5 vs. 43.0%; P=0.020) than those with low expressions. Nevertheless, only in the high CREPT subgroup did adjuvant therapy (AT) prolong the OS (5-year OS: 53.8 vs. 28.9%; P=0.020), especially for adjuvant radiotherapy (ART) (5-year OS: 85.7 vs. 28.9%; P=0.037; 5-year DFS: 85.7 vs. 22.3%; P=0.020). Surprisingly, high CREPT expressions endowed CCRT-treated patients with higher complete response rates (50% vs. 26%; P=0.018) and a favorable OS (3-year OS: 54.3 vs. 28.1%; P=0.046) compared to low expression. Overall, our findings indicate that CREPT is highly expressed in ESCC tissue compared with non-cancerous tissue and this feature is associated with a poor prognosis. Otherwise, patients with high CREPT expression were more sensitive to AT and CCRT. Moreover, CREPT could be a predictive immunohistochemical biomarker used to guide individualized clinical treatment.