Prognostic and Predictive Biomarkers in Patients with Locally Advanced Rectal Cancer (LARC) Treated with Preoperative Chemoradiotherapy

Somatic pharmacogenomics in the treatment prognosis of locally advanced rectal cancer patients: a narrative review of the literature

INTRODUCTION

Standard treatment for patients with locally advanced rectal cancer (LARC) includes neoadjuvant chemoradiotherapy (nCRT) with fluoropyrimidines, followed by surgical excision. The newly introduced therapeutic strategies propose intensified regimens or more conservative approaches based on risk stratification algorithms that currently include clinicoradiological criteria but not molecular variables. How to better stratify patients is a burning clinical question, and pharmacogenomics may prove useful in identifying new genetic markers that could be incorporated into clinical algorithms to personalize nCRT. An emerging area could be the evaluation of somatic mutations as potential genetic markers that correlate with patient prognosis. Tumor mutations in the RAS/BRAF genes, as well as microsatellite instability (MSI) status, are currently used in treatment selection for colorectal cancer (CRC); however, their clinical value in LARC is still unclear.

AREA COVERED

This literature review discusses the relevant findings on the prognostic role of mutations in the key oncogenes RAS, KRAS, BRAF, PIK3CA, SMAD4 and TP53, including MSI status in LARC patients treated with nCRT.

EXPERT OPINION

KRAS proved to be the most promising marker, consistently associated with poorer disease-free survival and overall survival. Therefore, KRAS could be a good candidate for integration into the risk stratification algorithm to develop a personalized treatment.

Prognostic value of lymphocytes in patients with breast cancer receiving radiotherapy after breast-conserving surgery: A post hoc analysis of a phase III randomized trial

PURPOSE

To evaluate the prognostic value of peripheral lymphocyte count (PLC) in the breast cancer patients after breast-conserving surgery (BCS) with radiotherapy (RT).

METHODS AND MATERIALS

This post hoc analysis was performed using data of 628 patients from a phase III, randomized controlled trial comparing hypofractionated RT (HFRT) with conventional fractionated RT (CFRT) after BCS. PLCs were obtained before, during, and after RT until the 1-year follow-up. The optimal cut-off PLCs were determined using the maxstat package in R. Survival rates were estimated using the Kaplan-Meier method and compared with the log-rank test.

RESULTS

A total of 275 (46.1 %) patients developed lymphopenia during RT, among them, 17 (2.8 %) had grade 3 lymphopenia and no one developed grade 4 lymphopenia. With a median follow-up of 110.8 months, patients with pre-RT PLCs of < 1.77 × 109/L had a significantly lower 10-year breast cancer-specific survival (BCSS) rate (P = 0.013) and overall survival (OS) rate (P = 0.026). Patients with a nadir PLC of < 1.35 × 109/L had a significantly poorer 10-year OS rate (P = 0.048). Multivariate analysis showed that a pre-RT PLC of < 1.77 × 109/L was an independent factor influencing BCSS and OS, while the effect of the nadir PLC did not remain significant. Neither PLC nor lymphopenia recovery at post-RT 1, 3, and 6 months and 1 year was associated with survival.

CONCLUSIONS

Radiation-induced lymphopenia in patients with breast cancer after BCS tends to be mild. The lower pre-RT PLC predicted poorer survival.

Assessing circulating tumour DNA (ctDNA) as a prognostic biomarker in locally advanced rectal cancer: a systematic review and meta-analysis

INTRODUCTION

Circulating tumour DNA (ctDNA) has emerged as a promising biomarker in various cancer types, including locally advanced rectal cancer (LARC), offering potential insights into disease progression, treatment response and recurrence. This review aims to comprehensively evaluate the utility of ctDNA as a prognostic biomarker in LARC.

METHODS

PubMed, EMBASE and Web of Science were searched as part of our review. Studies investigating the utility of ctDNA in locally advanced rectal cancer (LARC) were assessed for eligibility. Quality assessment of included studies was performed using the Newcastle Ottawa Scale (NOS) risk of bias tool. Outcomes extracted included basic participant characteristics, ctDNA details and survival data. A meta-analysis was performed on eligible studies to determine pooled recurrence-free survival (RFS).

RESULTS

Twenty-two studies involving 1676 participants were included in our analysis. Methodological quality categorised by the Newcastle Ottawa Scale was generally satisfactory across included studies. ctDNA detected at various time intervals was generally associated with poor outcomes across included studies. Meta-analysis demonstrated a pooled hazard ratio of 8.87 (95% CI 4.91-16.03) and 15.15 (95% CI 8.21-27.95), indicating an increased risk of recurrence with ctDNA positivity in the post-neoadjuvant and post-operative periods respectively.

CONCLUSION

Our systematic review provides evidence supporting the prognostic utility of ctDNA in patients with LARC, particularly in identifying patients at higher risk of disease recurrence in the post-neoadjuvant and post-operative periods.

Expression of Mitochondrial Long Non-Coding RNAs, MDL1 and MDL1AS, Are Good Prognostic and/or Diagnostic Biomarkers for Several Cancers, Including Colorectal Cancer

Non-coding RNAs provide new opportunities to identify biomarkers that properly classify cancer patients. Here, we study the biomarker status of the mitochondrial long non-coding RNAs, MDL1 and MDL1AS. Expression of these genes was studied in public transcriptomic databases. In addition, a cohort of 69 locally advanced rectal cancer (LARC) patients with a follow-up of more than 5 years was used to determine the prognostic value of these markers. Furthermore, cell lines of colorectal (HCT116) and breast (MDA-MB-231) carcinoma were employed to study the effects of downregulating MDL1AS in vitro. Expression of MDL1AS (but not MDL1) was significantly different in tumor cells than in the surrounding tissue in a tumor-type-specific context. Both MDL1 and MDL1AS were accurate biomarkers for the 5-year survival of LARC patients (p = 0.040 and p = 0.007, respectively) with promising areas under the curve in the ROC analyses (0.820 and 0.930, respectively). MDL1AS downregulation reduced mitochondrial respiration in both cell lines. Furthermore, this downregulation produced a decrease in growth and migration on colorectal cells, but the reverse effects on breast cancer cells. In summary, MDL1 and MDL1AS can be used as reliable prognostic biomarkers of LARC, and MDL1AS expression provides relevant information on the diagnosis of different cancers.

Construction and validation of a progression prediction model for locally advanced rectal cancer patients received neoadjuvant chemoradiotherapy followed by total mesorectal excision based on machine learning

Background

We attempted to develop a progression prediction model for local advanced rectal cancer(LARC) patients who received preoperative neoadjuvant chemoradiotherapy(NCRT) and operative treatment to identify high-risk patients in advance.

Methods

Data from 272 LARC patients who received NCRT and total mesorectal excision(TME) from 2011 to 2018 at the Fourth Hospital of Hebei Medical University were collected. Data from 161 patients with rectal cancer (each sample with one target variable (progression) and 145 characteristic variables) were included. One Hot Encoding was applied to numerically represent some characteristics. The K-Nearest Neighbor (KNN) filling method was used to determine the missing values, and SmoteTomek comprehensive sampling was used to solve the data imbalance. Eventually, data from 135 patients with 45 characteristic clinical variables were obtained. Random forest, decision tree, support vector machine (SVM), and XGBoost were used to predict whether patients with rectal cancer will exhibit progression. LASSO regression was used to further filter the variables and narrow down the list of variables using a Venn diagram. Eventually, the prediction model was constructed by multivariate logistic regression, and the performance of the model was confirmed in the validation set.

Results

Eventually, data from 135 patients including 45 clinical characteristic variables were included in the study. Data were randomly divided in an 8:2 ratio into a data set and a validation set, respectively. Area Under Curve (AUC) values of 0.72 for the decision tree, 0.97 for the random forest, 0.89 for SVM, and 0.94 for XGBoost were obtained from the data set. Similar results were obtained from the validation set. Twenty-three variables were obtained from LASSO regression, and eight variables were obtained by considering the intersection of the variables obtained using the previous four machine learning methods. Furthermore, a multivariate logistic regression model was constructed using the data set; the ROC indicated its good performance. The ROC curve also verified the good predictive performance in the validation set.

Conclusions

We constructed a logistic regression model with good predictive performance, which allowed us to accurately predict whether patients who received NCRT and TME will exhibit disease progression.

Risk-factors for locally advanced rectal cancer relapse after neoadjuvant chemoradiotherapy: A single center experience

The overall prognosis of locally advanced rectal cancer (LARC) remains unsatisfactory due to a high incidence of disease relapse. The present understanding of the factors that determine the likelihood of recurrence is limited or ineffective. We aimed to identify the main risk factors influencing tumor relapse in LARC patients after neoadjuvant chemoradiotherapy (nCRT) and surgical treatment in a single center in Republika Srpska. Patients with stage II or stage III who received nCRT before surgery for primary rectal cancer at the Oncology Clinic, University Clinical Center of Republika Srpska from January 2017 and December 2022 were included in the study. We collected patient demographics, clinical stage and characteristics, neoadjuvant therapy, and surgical methods, along with the pathological response after treatment completion, and analyzed them to identify the risk factors for tumor relapse. Out of 109 patients diagnosed with LARC, 34 (31,2%) had tumor relapse. The median time to relapse was 54 months. Participants with clinical T4 stage had a significantly shorter relapse time compared to the patients with clinical T2/3 stage. Subjects with positive lymph nodes removed, perivascular and perineural invasion, intraoperative perforation and patients without ypN stage improvement had significantly shorter time to relapse. Subjects with T4 stage had more than 4 times higher risk of relapse than patients with clinical T2/3 stage. Higher clinical T stage was an essential risk factor for tumor relapse in LARC patients after nCRT and surgical treatment. Comprehensive understanding and identification of the risk factors for tumor relapse in LARC patients are crucial for improving their long-term outcomes.