Sensitivity of Various Evaluating Modalities for Predicting a Pathologic Complete Response After Preoperative Chemoradiation Therapy for Locally Advanced Rectal Cancer

Predicting Neoadjuvant Chemoradiotherapy Response in Locally Advanced Rectal Cancer Using Tumor-Infiltrating Lymphocytes Density

PURPOSE

Accumulating evidence revealed the predictive value of tumor-infiltrating lymphocytes (TILs) for neoadjuvant chemoradiotherapy (nCRT) response in solid tumors. This study quantified TILs density using hematoxylin and eosin (H&E) stained whole-slide images (WSIs) and investigated the predictive value of TILs density on nCRT response in locally advanced rectal cancer (LARC) patients.

PATIENTS AND METHODS

Two hundred and ten patients diagnosed with LARC were enrolled in this study. The density of TILs in the stroma region was quantified by a semi-automatic method in WSIs. Patients were stratified into low-TILs and high-TILs groups using the median value as the threshold. The tumor regression grade (TRG) was used to assess the response to nCRT in tumor resected specimens. Based on TRG, patients were classified into major-responder (TRG 0-1) and non-responder (TRG 2-3) groups.

RESULTS

The TILs density was significantly correlated with the nCRT response. Specifically, patients with high-TILs tend to have a higher major-responder rate than the low-TILs group (63.8% vs 47.6%, P = 0.026). Univariate analysis showed the TILs density was a predictor for the nCRT response (high vs low, odds ratio [OR] =1.94, 95% confidence interval 1.12-3.37, P = 0.019), and multivariate analysis further confirmed the correlation (adjusted odds ratio [AOR] = 2.41, 1.28-4.56, P = 0.007).

CONCLUSION

Patients with a high-TIL density have a higher major-responder rate than the low-TILs group, indicating patients with a strong immune response benefit more from nCRT. This semi-automatic method can facilitate the individualized preoperative prediction of the TRG for LARC patients before nCRT.

Comparison between Local Excision and Radical Resection for the Treatment of Rectal Cancer in ypT0-1 Patients: An Analysis of the Clinicopathological Factors and Survival Rates

Tumors with good response to preoperative chemoradiotherapy have a favorable prognosis, and these findings raise interest in rectum-sparing strategies. This study aimed to compare the oncologic outcome between local excision and radical resection in ypT0-1 patients and to analyze prognostic factors. Patients with primary rectal cancer diagnosed with ypT0-1 after PCRT followed by either radical resection (RR) or local excision (LE) between 2005 and 2014 were included in this study (LE = 78, RR = 442). Clinicopathologic features, recurrence-free survival (RFS), and OS were analyzed. There was no statistically significant difference in the RFS and OS between the LE and RR groups. Clinical T stage (cT3-4) before PCRT was related to RFS and in the LE group (p = 0.022). Lymph node metastasis (HR: 4.884, 95% confidence interval: 2.451-9.732, p < 0.001) in the final pathology was the only factor associated with RFS, showing a statistically significant difference in the RR group. Lymph node metastasis and age were associated with OS in the RR group. This study confirms the oncologic feasibility of LE in ypT0-1 rectal cancer after PCRT. Additionally, careful patient selection with higher accuracy modalities should be updated to improve treatment outcomes of LE.

A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer

Preoperative chemoradiotherapy (PCRT) and subsequent surgery is the standard multimodal treatment for locally advanced rectal cancer (LARC), albeit PCRT response varies among the individuals. This creates a dire necessity to identify a predictive model to forecast treatment response outcomes and identify patients who would benefit from PCRT. In this study, we performed a gene expression study using formalin-fixed paraffin-embedded (FFPE) tumor biopsy samples from 156 LARC patients (training cohort n = 60; validation cohort n = 96); we identified the nine-gene signature (FGFR3, GNA11, H3F3A, IL12A, IL1R1, IL2RB, NKD1, SGK2, and SPRY2) that distinctively differentiated responders from non-responders in the training cohort (accuracy = 86.9%, specificity = 84.8%, sensitivity = 81.5%) as well as in an independent validation cohort (accuracy = 81.0%, specificity = 79.4%, sensitivity = 82.3%). The signature was independent of all pathological and clinical features and was robust in predicting PCRT response. It is readily applicable to the clinical setting using FFPE samples and Food and Drug Administration (FDA) approved hardware and reagents. Predicting the response to PCRT may aid in tailored therapies for respective responders to PCRT and improve the oncologic outcomes for LARC patients.