Patients with Non-response to Neoadjuvant Chemoradiation for Esophageal Cancer Have No Survival Advantage over Patients Undergoing Primary Esophagectomy

A combined nomogram based on radiomics and hematology to predict the pathological complete response of neoadjuvant immunochemotherapy in esophageal squamous cell carcinoma

BACKGROUND

To predict pathological complete response (pCR) in patients receiving neoadjuvant immunochemotherapy (nICT) for esophageal squamous cell carcinoma (ESCC), we explored the factors that influence pCR after nICT and established a combined nomogram model.

METHODS

We retrospectively included 164 ESCC patients treated with nICT. The radiomics signature and hematology model were constructed utilizing least absolute shrinkage and selection operator (LASSO) regression, and the radiomics score (radScore) and hematology score (hemScore) were determined for each patient. Using the radScore, hemScore, and independent influencing factors obtained through univariate and multivariate analyses, a combined nomogram was established. The consistency and prediction ability of the nomogram were assessed utilizing calibration curve and the area under the receiver operating factor curve (AUC), and the clinical benefits were assessed utilizing decision curve analysis (DCA).

RESULTS

We constructed three predictive models.The AUC values of the radiomics signature and hematology model reached 0.874 (95% CI: 0.819-0.928) and 0.772 (95% CI: 0.699-0.845), respectively. Tumor length, cN stage, the radScore, and the hemScore were found to be independent factors influencing pCR according to univariate and multivariate analyses (P < 0.05). A combined nomogram was constructed from these factors, and AUC reached 0.934 (95% CI: 0.896-0.972). DCA demonstrated that the clinical benefits brought by the nomogram for patients across an extensive range were greater than those of other individual models.

CONCLUSIONS

By combining CT radiomics, hematological factors, and clinicopathological characteristics before treatment, we developed a nomogram model that effectively predicted whether ESCC patients would achieve pCR after nICT, thus identifying patients who are sensitive to nICT and assisting in clinical treatment decision-making.

Pathologic complete response in patients with esophageal cancer receiving neoadjuvant chemotherapy or chemoradiation: A systematic review and meta-analysis

BACKGROUND

Neoadjuvant chemoradiation and chemotherapy are recommended for the treatment of nonmetastatic esophageal cancer. The benefit of neoadjuvant treatment is mostly limited to patients who exhibit pathologic complete response (pCR). Existing estimates of pCR rates among patients receiving neoadjuvant therapy have not been synthesized and lack precision.

METHODS

We conducted an independently funded systematic review and meta-analysis (PROSPERO CRD42023397402) of pCR rates among patients diagnosed with esophageal cancer treated with neoadjuvant chemo(radiation). Studies were identified from Medline, EMBASE, and CENTRAL database searches. Eligible studies included trials published from 1992 to 2022 that focused on nonmetastatic esophageal cancer, including the gastroesophageal junction. Histology-specific pooled pCR prevalence was determined using the Freeman-Tukey transformation and a random effects model.

RESULTS

After eligibility assessment, 84 studies with 6451 patients were included. The pooled prevalence of pCR after neoadjuvant chemotherapy in squamous cell carcinomas was 9% (95% CI: 6%-14%), ranging from 0% to 32%. The pooled prevalence of pCR after neoadjuvant chemoradiation in squamous cell carcinomas was 32% (95% CI: 26%-39%), ranging from 8% to 66%. For adenocarcinoma, the pooled prevalence of pCR was 6% (95% CI: 1%-12%) after neoadjuvant chemotherapy, and 22% (18%-26%) after neoadjuvant chemoradiation.

CONCLUSIONS

Under one-third of patients with esophageal cancer who receive neoadjuvant chemo(radiation) experience pCR. Patients diagnosed with squamous cell carcinomas had higher rates of pCR than those with adenocarcinomas. As pCR represents an increasingly utilized endpoint in neoadjuvant trials, these estimates of pooled pCR rates may serve as an important benchmark for future trial design.

Induction FOLFOX and PET-Directed Chemoradiation for Locally Advanced Esophageal Adenocarcinoma

OBJECTIVE

To compare the efficacy and safety of induction FOLFOX followed by PET-directed nCRT, induction CP followed by PET-directed nCRT, and nCRT with CP alone in patients with EAC.

SUMMARY OF BACKGROUND DATA

nCRT with CP is a standard treatment for locally advanced EAC. The results of cancer and leukemia group B 80803 support the use of induction chemotherapy followed by PET-directed chemo-radiation therapy.

METHODS

We retrospectively identified all patients with EAC who underwent the treatments above followed by esophagectomy. We assessed incidences of pathologic complete response (pCR), near-pCR (ypN0 with ≥90% response), and surgical complications between treatment groups using Fisher exact test and logistic regression; disease-free survival (DFS) and overall survival (OS) were estimated by the Kaplan-Meier method and evaluated using the log-rank test and extended Cox regression.

RESULTS

In total, 451 patients were included: 309 (69%) received induction chemotherapy before nCRT (FOLFOX, n = 70; CP, n = 239); 142 (31%) received nCRT with CP. Rates of pCR (33% vs. 16%, P = 0.004), near-pCR (57% vs. 33%, P < 0.001), and 2-year DFS (68% vs. 50%, P = 0.01) were higher in the induction FOLFOX group than in the induction CP group. Similarly, the rate of near-pCR (57% vs. 42%, P = 0.04) and 2-year DFS (68% vs. 44%, P < 0.001) were significantly higher in the FOLFOX group than in the no-induction group.

CONCLUSIONS

Induction FOLFOX followed by PET-directed nCRT may result in better histopathologic response rates and DFS than either induction CP plus PET-directed nCRT or nCRT with CP alone.

Pathological complete response in multimodal treatment of esophageal cancer: a retrospective cohort study

To evaluate pathological complete response (pCR, ypT0ypN0) after neoadjuvant treatment compared with non-complete response (non-CR) in patients with esophageal cancer (EC), and 393 patients were retrospectively analyzed. Survival probability was analyzed in patients with: (i) pCR vs non-CR; (ii) complete response of the primary tumor but persisting lymphatic metastases (non-CR-T0N+) and (iii) pCR and tumor-free lymphnodes exhibiting signs of postneoadjuvant regression vs. no signs of regression. (i) Median overall survival (mOS) was favorable in patients with pCR (pCR: mOS not reached vs. non-CR: 41 months, P < 0.001). Multivariate analysis revealed that grade of regression was not an independent predictor for prolonged survival. Instead, the achieved postneoadjuvant TNM-stage (T-stage: Hazard ratio [HR] ypT3-T4 vs. ypT0-T2: 1.837; N-stage: HR ypN1-N3 vs. ypN0: 2.046; Postneoadjuvant M-stage: HR ypM1 vs. ycM0: 2.709), the residual tumor (R)-classification (HR R1 vs. R0: 4.195) and the histologic subtype of EC (HR ESCC vs. EAC: 1.688) were prognostic factors. Patients with non-CR-T0N+ have a devastating prognosis, similar to those with local non-CR and lymphatic metastases (non-CR-T + N+) (non-CR-T0N+: 22.0 months, non-CR-T + N-: mOS not reached, non-CR-T + N+: 23.0 months; P-values: non-CR-T0N+ vs. non-CR-T + N-: 0.016; non-CR-T0N+ vs. non-CR-T + N+: 0.956; non-CR-T + N- vs. non-CR-T + N+: <0.001). Regressive changes in lymphnodes after neoadjuvant treatment did not influence survival-probability in patients with pCR (mOS not reached in each group; EAC-patients: P = 0.0919; ESCC-patients: P = 0.828). Particularly, the achieved postneoadjuvant ypTNM-stage influences the survival probability of patients with EC. Patients with non-CR-T0N+ have a dismal prognosis, and only true pathological complete response with ypT0ypN0 offers superior survival probabilities.

Applying post-neoadjuvant pathologic stage as prognostic tool in esophageal squamous cell carcinoma

BACKGROUND

It is still uncertain whether the newly released eighth American Joint Committee on Cancer (AJCC) post-neoadjuvant pathologic (yp) tumor-node-metastasis (TNM) stage for esophageal carcinoma can perform well regarding patient stratification. The current study aimed to assess the prognostication ability of the eighth AJCC ypTNM staging system and attempted to explore how to facilitate the staging system for more effective evaluation of prognosis.

MATERIALS AND METHODS

A total of 486 patients treated with neoadjuvant radiotherapy/chemoradiotherapy (nRT/CRT) were enrolled. ypN stage was reclassified by recursive partitioning. Prognostic performance, monotonicity, homogeneity, and discriminatory of yp and modified yp (myp) staging systems were assessed by time-dependent receiver operating characteristic (ROC), linear trend log-rank test, likelihood ratio χ2 test, Harrell's c statistic, and Akaike information criterion (AIC).

RESULTS

The ypT stage, ypN stage, and pathologic response were significant prognostic factors of overall survival. Survival was not discriminated well using the eighth AJCC ypN stage and ypTNM stage. Recursive partitioning reclassified mypN0-N2 as metastasis in 0, 1-2, and ≥3 regional lymph nodes. Applying the ypT stage, mypN stage, and pathologic response to construct the myp staging system, the myp stage performed better in time-dependent ROC, linear trend log-rank test, likelihood ratio χ2 test, Harrell's c statistic, and AIC.

CONCLUSIONS

The eighth AJCC ypTNM staging system performed well in differentiating prognosis to some extent. By reclassifying the ypN stage and enrolling pathologic response as a staging element, the myp staging system holds significant potential for prognostic discrimination.

Prediction of Non-Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer Patients with 18F-FDG PET Radiomics Based Machine Learning Classification

Background: Approximately 26% of esophageal cancer (EC) patients do not respond to neoadjuvant chemoradiotherapy (nCRT), emphasizing the need for pre-treatment selection. The aim of this study was to predict non-response using a radiomic model on baseline ¹⁸F-FDG PET. Methods: Retrospectively, 143 ¹⁸F-FDG PET radiomic features were extracted from 199 EC patients (T1N1-3M0/T2–4aN0-3M0) treated between 2009 and 2019. Non-response (n = 57; 29%) was defined as Mandard Tumor Regression Grade 4–5 (n = 44; 22%) or interval progression (n = 13; 7%). Randomly, 139 patients (70%) were allocated to explore all combinations of 24 feature selection strategies and 6 classification methods towards the cross-validated average precision (AP). The predictive value of the best-performing model, i.e AP and area under the ROC curve analysis (AUC), was evaluated on an independent test subset of 60 patients (30%). Results: The best performing model had an AP (mean ± SD) of 0.47 ± 0.06 on the training subset, achieved by a support vector machine classifier trained on five principal components of relevant clinical and radiomic features. The model was externally validated with an AP of 0.66 and an AUC of 0.67. Conclusion: In the present study, the best-performing model on pre-treatment ¹⁸F-FDG PET radiomics and clinical features had a small clinical benefit to identify non-responders to nCRT in EC.

Identification of MTHFD2 as a novel prognosis biomarker in esophageal carcinoma patients based on transcriptomic data and methylation profiling

DNA methylation is an important epigenetic regulatory mechanism in esophageal carcinoma (EC) and is associated with genomic instability and carcinogenesis. In the present study, we aimed to identify tumor biomarkers for predicting prognosis of EC patients.We downloaded mRNA expression profiles and DNA methylation profiles associated with EC from the Gene Expression Omnibus database. Differentially expressed and differentially methylated genes between tumor tissues and adjacent normal tissue samples were identified. Functional enrichment analyses were performed, followed by the construction of protein-protein interaction networks. Data were validated based on methylation profiles from The Cancer Genome Atlas. Candidate genes were further verified according to survival analysis and Cox regression analysis.We uncovered multiple genes with differential expression or methylation in tumor samples compared with normal samples. After taking the intersection of 3 differential gene sets, we obtained a total of 232 overlapping genes. Functional enrichment analysis revealed that these genes are related to pathways such as "glutathione metabolism," "p53 signaling pathway," and "focal adhesion." Furthermore, 8 hub genes with inversed expression and methylation correlation were identified as candidate genes. The abnormal expression levels of MSN, PELI1, and MTHFD2 were correlated with overall survival times in EC patients (P < .05). Only MTHFD2 was significantly associated with a pathologic stage according to univariate analysis (P = .037) and multivariate analysis (P = .043).Our study identified several novel EC biomarkers with prognostic value by integrated analysis of transcriptomic data and methylation profiles. MTHFD2 could serve as an independent biomarker for predicting prognosis and pathological stages of EC.