Integrating tumor regression and nodal status for refined prognostication after neoadjuvant therapy in esophageal cancer: where does TRG-N fit in the evolving global landscape?

The recent study based on the Netherlands Cancer Registry proposing a novel tumor regression grade-nodal status classification (TRG-N) prognostic classification for esophageal cancer undergoing neoadjuvant therapy followed by esophagectomy offers a timely attempt to refine post-treatment risk stratification in a real-world, population-based cohort (1). By combining tumor regression grade (TRG) and nodal status in a single framework, the authors address a familiar clinical dilemma: two patients with the same post-neoadjuvant tumor-node-metastasis stage (ypTNM) category may have very different degrees of treatment response and residual tumor biology. The appeal of TRG-N lies in its conceptual simplicity—capturing both primary tumor sensitivity to neoadjuvant therapy and the enduring prognostic weight of lymphatic spread—and its potential to serve as a pragmatic bridge between detailed pathology and bedside decision-making.

The reported results suggest that TRG-N provides incremental prognostic discrimination beyond conventional ypTNM staging, particularly in esophageal squamous cell carcinoma (ESCC). This is biologically plausible, as ESCC is generally more sensitive to chemoradiotherapy than adenocarcinoma (AC), and regression-based metrics can meaningfully stratify outcomes within the same anatomic stage. In AC, the comparison appears more nuanced, with some metrics favoring TRG-N while others remain comparable or even slightly inferior to ypTNM. A classification that performs strongly in squamous cell carcinoma (SCC)-dominant, chemoradiation-heavy settings may require recalibration where perioperative or triplet chemotherapy is more commonly used.

An important strength of the registry approach is that it reflects routine practice rather than the tightly controlled selection of clinical trials. As minimally invasive esophagectomy (MIE) has become increasingly prevalent worldwide, staging systems must remain robust across evolving operative techniques and perioperative pathways (2). The high proportion of thoracoscopic and robotic procedures in the Dutch cohort mirrors global trends and reassures us that TRG-N is being evaluated in a modern surgical environment. This is consistent with Japanese and broader East Asian data supporting the safety and oncologic acceptability of MIE. Notably, the phase III JCOG1409 MONET trial—the first large, multicenter randomized controlled trial (RCT) to evaluate overall survival as the primary endpoint between thoracoscopic and open transthoracic esophagectomy—confirmed the non-inferiority of thoracoscopic esophagectomy for clinical stage I–III thoracic esophageal cancer and demonstrated favorable short-term respiratory outcomes (3). These data support thoracoscopic esophagectomy as a standard treatment comparable with open surgery and lend external validity to the Dutch experience.

A key question is how TRG-N might be adopted across different neoadjuvant strategies. In the Dutch series, neoadjuvant chemoradiotherapy (nCRT) predominates, consistent with the widespread adoption of CROSS-type protocols in Western practice (4). In Japan, however, the standard landscape for locally advanced ESCC has evolved rapidly. The JCOG1109 (NExT) trial demonstrated a statistically significant overall survival benefit of neoadjuvant triplet chemotherapy [docetaxel, cisplatin, and fluorouracil (DCF)] compared with doublet therapy, with a 3-year overall survival of 72.1% versus 62.6% [hazard ratio (HR): 0.68] (5). This pivotal trial established DCF-based neoadjuvant chemotherapy as a new standard option in fit patients. For TRG-N, this implies that a regression-nodal classification validated predominantly in nCRT-treated cohorts must now be assessed in chemotherapy-dominant settings. Tumor regression patterns after DCF may not mirror those after radiation-containing regimens, and the distribution of TRG categories could shift accordingly. Rather than asking whether TRG-N is universally “better” than ypTNM, the next step is to test whether its structure can be preserved while calibrating cut-offs or category definitions to specific neoadjuvant backbones.

Risk stratification after neoadjuvant therapy directly influences postoperative surveillance and consideration of adjuvant interventions. The post-CROSS era has already seen the introduction of adjuvant immunotherapy for residual disease in selected settings, and ongoing trials continue to explore perioperative immune and targeted strategies. As systemic options expand, the clinical utility of refined pathologic classifications will increasingly be judged not only by prognostic separation but also by their ability to identify patients most likely to benefit from treatment escalation or de-escalation. In this context, the concept of minimal residual disease (MRD) is gaining attention in esophageal cancer, particularly with the emergence of circulating tumor DNA (ctDNA)-based assays (6). After effective induction therapy and curative-intent surgery, small-volume, therapy-resistant disease may persist despite apparently favorable anatomic findings, ultimately driving recurrence. Postoperative pathology can therefore be viewed as an indirect readout of MRD biology, especially when molecular tests are unavailable or not yet standardized.

The TRG-N classification aligns well with this MRD-oriented perspective. TRG provides a structured estimate of residual viable tumor in the primary lesion, whereas ypN captures residual disease in the lymphatic compartment, a key surrogate of persistent systemic risk. Patients in higher TRG-N stages may be those most likely to harbor clinically meaningful MRD and thus may be candidates for intensified surveillance or adjuvant therapy, whereas those with excellent regression and ypN0 status could be considered for more individualized, less burdensome follow-up.

Nodal status remains the cornerstone of post-treatment prognosis in esophageal cancer, and combining TRG with nodal categories is consistent with accumulating evidence emphasizing the quantitative dimension of lymph node assessment. Our recent meta-analysis demonstrated that maximizing the number of dissected lymph nodes improves staging accuracy and survival outcomes and that the lymph node ratio (LNR) is a valuable prognostic factor that may guide postoperative therapy decisions (7). These findings highlight an important nuance for TRG-N: its accuracy and clinical credibility depend on high-quality lymphadenectomy and meticulous pathologic evaluation. A nodal component cannot function optimally if node retrieval is inadequate. This is especially relevant in MIE and robotic settings, where technical excellence can facilitate comprehensive nodal clearance but variability in learning curves and institutional volume may still influence node yield. In the longer term, TRG-N could evolve into a platform that interacts with lymph node dissection (LND) and LNR, leading to multidimensional nomograms that integrate regression, nodal burden, and surgical quality.

The idea of integrating TRG and ypN is not unique to esophageal cancer and appears conceptually robust across upper gastrointestinal malignancies. A recent large, multicenter analysis in gastric cancer proposed an ypN-TRG staging system constructed using the “metro-ticket” paradigm, in which the combination of ypN stage and Becker TRG grade was translated into a continuous score and then grouped into five sub-stages (8). This ypN-TRG system demonstrated superior predictive performance compared with American Joint Committee on Cancer (AJCC) eighth edition ypTNM in terms of C-index and Akaike information criterion (AIC)/Bayesian information criterion (BIC), and its superiority was confirmed in an external validation cohort (8). Together with the esophageal TRG-N work by Wang et al. (1), these findings suggest that “regression plus nodes” is an attractive and repeatable principle for post-neoadjuvant staging in both gastric and esophageal cancer, even though the exact mathematical formulation may differ.

Several practical considerations will shape the clinical adoption of TRG-N. First, global standardization of TRG assessment remains imperfect. Different grading systems [Mandard, Becker, College of American Pathologists (CAP), and others] vary in definitions and interobserver reproducibility. A TRG-N framework must clarify how TRG should be measured and whether it is portable across grading systems or requires a single standardized method. Second, integration into routine reporting workflows is essential. Pathology templates that already include TRG and ypN could incorporate TRG-N categories with minimal additional burden, but formal endorsement by professional societies or guideline committees would greatly facilitate this process (9,10). Third, we must determine whether TRG-N provides actionable thresholds. For example, does a high-risk TRG-N subgroup predict benefit from adjuvant systemic therapy beyond existing indications? Conversely, could an excellent-response, node-negative subgroup safely undergo de-escalated surveillance? Addressing these questions will determine whether TRG-N is merely prognostic or truly decision-changing.

From the viewpoint of contemporary surgical oncology, perhaps the most attractive feature of TRG-N is that it encourages multidisciplinary thinking. It asks surgeons, medical oncologists, and pathologists to interpret post-treatment pathology as an integrated narrative of resistance and response rather than as isolated anatomic descriptors. In doing so, it reframes postoperative discussion from “what stage is it?” to “what biology remains?”, a shift that is well aligned with the direction of precision oncology. The classification also complements the trend toward registry-driven benchmarking, where real-world data can rapidly validate and refine predictive tools across diverse practice settings.

In summary, the TRG-N classification derived from the Netherlands Cancer Registry represents an important step toward a more response-aware and node-integrated approach to post-neoadjuvant staging in esophageal cancer. Its particularly strong performance in ESCC is encouraging and may have broad relevance for regions with high SCC prevalence. At the same time, the evolving therapeutic landscape—exemplified by Japan’s adoption of neoadjuvant DCF based on JCOG1109 and the establishment of thoracoscopic esophagectomy as a standard approach supported by JCOG1409 (3,5)—highlights the need for regimen- and region-specific validation. Coupled with evidence emphasizing the prognostic importance of adequate lymph node dissection and the complementary role of LNR (7), and with parallel developments of ypN-TRG systems in gastric cancer (8), TRG-N should be interpreted as a promising component of a broader strategy to integrate treatment response, surgical quality, and nodal biology.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Translational Cancer Research. The article has undergone external peer review.

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