Clinical Relevance of Major Pathologic Regression for Locally Advanced Rectal Cancer

This large-scale, multi-center cohort study aims to investigate the clinical and prognostic implications of histopathologic characteristics in patients with Locally Advanced Rectal Cancer (LARC) following Neoadjuvant Chemoradiotherapy (NCRT). The study will retrospectively and prospectively analyze data from consecutive LARC patients treated at participating institutions between 2016 and 2022.

Study Design and Objectives

Primary Objective:

To evaluate the clinical significance of Major Pathologic Regression (MPR) in LARC patients following NCRT. MPR is defined as ≤10% residual viable tumor within the tumor bed in the pathologic evaluation. The study will correlate MPR status with long-term survival outcomes, including Progression-Free Survival (PFS) and Overall Survival (OS), to determine its validity as a surrogate endpoint for treatment efficacy.

Secondary Objectives:

To compare the efficacy of different NCRT regimens (e.g., fluoropyrimidine-based vs. oxaliplatin-containing protocols) in achieving MPR and improving survival outcomes.

To assess the prognostic value of novel histopathologic parameters, such as tumor necrosis density (NECR-TD), tumor-infiltrating lymphocyte (TLS) density, and TLS-to-necrosis ratio (T/NR), in predicting DFS and OS.

Study Population

Inclusion Criteria:

Adults (≥18 years) diagnosed with locally advanced rectal adenocarcinoma (clinical stage II-III).

Completion of NCRT followed by curative-intent surgery. Availability of pre- and post-treatment histopathologic data, including standardized regression grading and digitized whole-slide images (WSIs).

Exclusion Criteria:

Metastatic disease at diagnosis. Incomplete clinical or pathologic records. Data Collection and Variables

Clinical Data:

Demographics, tumor stage ( ypTNM), NCRT regimen, surgical approach, recurrence, and survival outcomes.

Pathologic Data:

Regression Grading: Residual viable tumor percentage, necrosis extent, and lymph node regression (ypN-Reg+/-).

Quantitative Digital Pathology: AI-driven analysis of WSIs to compute NECR-TD, TLS-TD, and T/NR (Figure 1).

Follow-Up:

PFS and OS will be tracked for a minimum of 3 years post-surgery. Statistical Analysis

Survival Analysis:

Kaplan-Meier curves and Cox proportional hazards models will assess associations between MPR, histopathologic parameters, and survival outcomes.

Comparative Analysis:

Subgroup analyses will compare outcomes across NCRT regimens and LARC subtypes (e.g., mucinous vs. adenocarcinoma).

Machine Learning:

Prognostic models integrating clinical and histopathologic variables will be developed to predict DFS/OS.

Ethical Considerations The Institutional Review Boards (IRBs) of all participating centers have approved the study protocol.

Patient data will be anonymized, and informed consent will be waived for retrospective cohorts but obtained prospectively.

Innovation and Impact

This study addresses critical gaps in the prognostication of LARC by:

Validating MPR as a standardized endpoint for NCRT efficacy. Introducing quantitative, AI-driven histopathologic biomarkers (e.g., T/NR) to refine risk stratification.

Providing evidence for optimizing NCRT regimens based on tumor biology and regression patterns.

Results will be disseminated through peer-reviewed publications and clinical guidelines to improve personalized treatment strategies for LARC.