Exploring novel genetic and hematological predictors of response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer

Dose Escalation in Neoadjuvant Chemoradiotherapy for Rectal Cancer: Short-Term Efficacy and Toxicity of VMAT-SIB vs. 3D-CRT

Background and Objectives: The standard treatment for locally advanced rectal cancer (LARC) includes neoadjuvant chemoradiotherapy (nCRT), followed by surgery with or without adjuvant chemotherapy (CT). This study evaluated the efficacy and safety of dose-escalated radiotherapy (RT) using the volumetric modulated arc therapy-simultaneous integrated boost (VMAT-SIB) technique in patients with LARC compared to 3D conformal radiotherapy (3D-CRT). Materials and Methods: This study prospectively enrolled 75 patients with LARC. All patients received nCRT using VMAT-SIB, delivering a tumor dose (TD) of 54 Gy in 25 fractions, with concomitant CT following the 5-fluorouracil and leucovorin (5-FU-LV) protocol. To compare the treatment outcomes and toxicity associated with the increased RT dose, a retrospective cohort of 62 patients treated with the 3D-CRT technique was analyzed. The 3D-CRT group received a TD of 50.4 Gy in 28 fractions with the same CT. Outcomes, including pathological complete response (pCR), tumor regression grade (TRG), and sphincter preservation rates, were compared. Results: Among operated patients, the group treated with VMAT-SIB demonstrated improved rates of pCR (20.6% vs. 8.9%), with a statistically significant trend (p = 0.06). Sphincter-preserving surgeries were performed in 49 out of 63 operated patients (77.8%) in the VMAT-SIB group, compared to 35 out of 56 (62.5%) in the 3D-CRT group. Analysis of the definitive postoperative stage revealed a significantly higher prevalence of lower T categories (T0-2) (p < 0.01), negative N status (p < 0.05), and lower stages (I + II) (p < 0.05) in patients treated with the intensified RT approach. However, no significant differences in acute toxicity were observed. Conclusions: The implementation of intensified treatment with a higher dose using the VMAT-SIB technique demonstrated significant benefits in downsizing and downstaging compared to the standard treatment approach. These findings support its integration into clinical practice. However, further prospective, multi-center studies are needed to validate these results and assess long-term outcomes.

Pathomics-based machine learning models for predicting pathological complete response and prognosis in locally advanced rectal cancer patients post-neoadjuvant chemoradiotherapy: insights from two independent institutional studies

BACKGROUND

Accurate prediction of pathological complete response (pCR) and disease-free survival (DFS) in locally advanced rectal cancer (LARC) patients undergoing neoadjuvant chemoradiotherapy (NCRT) is essential for formulating effective treatment plans. This study aimed to construct and validate the machine learning (ML) models to predict pCR and DFS using pathomics.

METHOD

A retrospective analysis was conducted on 294 patients who received NCRT from two independent institutions. Pathomics from pre-NCRT H&E stains were extracted, and five ML models were developed and validated across two centers using ROC, Kaplan-Meier, time-dependent ROC, and nomogram analyses.

RESULT

Among the five ML models, the Xgboost (XGB) model demonstrated superior performance in predicting pCR, achieving an AUC of 1.000 (p < 0.001) on the internal data-set and an AUC of 0.950 (p = 0.001) on the external data-set.The XGB model effectively differentiated between high-risk and low-risk prognosis patients across all five centers: internal dataset (DFS, p = 0.002; OS, p = 0.004) and external dataset (DFS, p = 0.074; OS, p = 0.224).Furthermore, the COX regression demonstrated that the tumor length (HR = 1.230, 95%CI: 1.050-1.440, p = 0.010), post-NCRT CEA (HR = 1.716, 95%CI: 1.031- 2.858, p = 0.038), and XGB model score (HR = 0.128, 95%CI: 0.026-0.636, p = 0.012) were independent predictors of DFS after NCRT in the internal data-set.Using COX regression, the nomogram model and time-dependent AUC analysis demonstrated strong predictive discrimination for DFS in LARC patients across two independent institutions.

CONCLUSION

The ML model based on pathomics demonstrated effective prediction of pCR and prognosis in LARC patients. Further validation in larger cohorts is warranted to confirm the findings of this study.

Two Decades of Progress in Personalized Medicine of Colorectal Cancer in Serbia-Insights from the Institute for Oncology and Radiology of Serbia

BACKGROUND

It is projected that, by 2040, the number of new cases of colorectal cancer (CRC) will increase to 3.2 million, and the number of deaths to 1.6 million, highlighting the need for prevention strategies, early detection and adequate follow-up. In this study, we aimed to provide an overview of the progress in personalized medicine of CRC in Serbia, with results and insights from the Institute for Oncology and Radiology of Serbia (IORS), and to propose guidance for tackling observed challenges in the future.

METHODS

Epidemiological data were derived from official global and national cancer registries and IORS electronic medical records. Germline genetic testing for Lynch syndrome was performed by Next Generation Sequencing. RAS and BRAF mutation analyses were performed using qPCR diagnostic kits.

RESULTS

Epidemiology and risk factors, prevention and early detection programs, as well as treatment options and scientific advances have been described in detail. Out of 103 patients who underwent germline testing for Lynch syndrome, 19 (18.4%) showed a mutation in MMR genes with pathogenic or likely pathogenic significance and 8 (7.8%) in other CRC-associated genes (APC, CHEK2, MUTYH). Of 6369 tested patients, 50.43% had a mutation in KRAS or NRAS genes, while 9.54% had the V600 mutation in the BRAF gene.

CONCLUSIONS

Although significant improvements in CRC management have occurred globally in recent years, a strategic approach leading to population-based systemic solutions is required. The high incidence of young-onset CRC and the growing elderly population due to a rise in life expectancy will be especially important factors for countries with limited healthcare resources like Serbia.

Methylenetetrahydrofolate reductase polymorphic variants C677T and A1298C in rectal cancer in Slavic population: significance for cancer risk and response to chemoradiotherapy

Background: Methylenetetrahydrofolate reductase (MTHFR) single nucleotide polymorphisms (SNPs) have been suggested as risk, prognostic, and predictive factors for colorectal cancer in various populations, but have not been validated so far. The aim of this study was to examine the association of MTHFR C677T (rs1801133) and A1298C (rs1801131) single nucleotide polymorphisms with the risk of rectal cancer as well as the response to neoadjuvant chemoradiotherapy (nCRT) based on 5-Fluorouracil (5-FU)/leucovorin (LV) in the locally advanced setting. Patients and methods: This case-control study included 119 healthy controls and 97 patients with locally advanced rectal cancer (LARC). For MTHFR genotyping, restriction fragment length polymorphism analysis (PCR-RFLP) was employed. Results: In silico analysis highlighted that SNPs C677T and A1298T correlate with MTHFR gene expression, and that gene expression profile correlates with cancer risk and stage. Using dominant and recessive models, it was found that the MTHFR 677CC vs. 677CT+677TT have increased risk of cancer development (odds ratio (OR): 2.27; 95% confidence interval (CI): 1.30-3.95, p = 0.002) as well as 677CC+677CT compared to 677TT (OR: 4.18, 95% CI: 1.16-14.99, p = 0.014). MTHFR 1298AA also shown increased risk for cancer development compared to 1298AC+1298CC (OR:2.0, 95% CI: 1.20-3.59, p = 0.035) Statistical analysis of combined genotypes highlighted the protective role of CT/AC combined genotype (OR: 3.15 95% CI: 1.576-6.279, p = 0.002) while the CC/AA genotype showed an increased risk for rectal cancer development (OR: 2.499, 95% CI: 1.246-5.081, p = 0.016) The carriers of the 677C/1298A haplotype had the highest risk for developing rectal cancer (OR: 1.74; 95% CI: 1.198-2.530, p = 0.002) while the 677T/1298C haplotype seems to provide a protective effect. (OR: 0.44; 95%CI 0.248-0.795, p = 0.003). No significant association with response to chemoradiotherapy was found. Conclusion: Our data point to MTHFR 667C allele and 1298A alleles as low-penetrance risk factors for rectal cancer in our population. To the best of our knowledge, this is the first study of this type performed on the Slavic population in the Western Balkan, as various population-based factors might also be significant our findings can be used for future meta-analyses and the construction of genetic cancer risk prediction panels.

Performance and Dimensionality of Pretreatment MRI Radiomics in Rectal Carcinoma Chemoradiotherapy Prediction

(1) Background: This study aimed to develop a machine learning model based on radiomics of pretreatment magnetic resonance imaging (MRI) 3D T2W contrast sequence scans combined with clinical parameters (CP) to predict neoadjuvant chemoradiotherapy (nCRT) response in patients with locally advanced rectal carcinoma (LARC). The study also assessed the impact of radiomics dimensionality on predictive performance. (2) Methods: Seventy-five patients were prospectively enrolled with clinicopathologically confirmed LARC and nCRT before surgery. Tumor properties were assessed by calculating 2141 radiomics features. Least absolute shrinkage selection operator (LASSO) and multivariate regression were used for feature selection. (3) Results: Two predictive models were constructed, one starting from 72 CP and 107 radiomics features, and the other from 72 CP and 1862 radiomics features. The models revealed moderately advantageous impact of increased dimensionality, with their predictive respective AUCs of 0.86 and 0.90 in the entire cohort and 0.84 within validation folds. Both models outperformed the CP-only model (AUC = 0.80) which served as the benchmark for predictive performance without radiomics. (4) Conclusions: Predictive models developed in this study combining pretreatment MRI radiomics and clinicopathological features may potentially provide a routine clinical predictor of chemoradiotherapy responders, enabling clinicians to personalize treatment strategies for rectal carcinoma.

Data-Independent Acquisition Mass Spectrometry Analysis of FFPE Rectal Cancer Samples Offers In-Depth Proteomics Characterization of the Response to Neoadjuvant Chemoradiotherapy

Locally advanced rectal cancer (LARC) presents a challenge in identifying molecular markers linked to the response to neoadjuvant chemoradiotherapy (nCRT). This study aimed to utilize a sensitive proteomic method, data-independent mass spectrometry (DIA-MS), to extensively analyze the LARC proteome, seeking individuals with favorable initial responses suitable for a watch-and-wait approach. This research addresses the unmet need to understand the response to treatment, potentially guiding personalized strategies for LARC patients. Post-treatment assessment included MRI scans and proctoscopy. This research involved 97 LARC patients treated with intense chemoradiotherapy, comprising radiation and chemotherapy. Out of 97 LARC included in this study, we selected 20 samples with the most different responses to nCRT for proteome profiling (responders vs. non-responders). This proteomic approach shows extensive proteome coverage in LARC samples. The analysis identified a significant number of proteins compared to a prior study. A total of 915 proteins exhibited differential expression between the two groups, with certain signaling pathways associated with response mechanisms, while top candidates had good predictive potential. Proteins encoded by genes SMPDL3A, PCTP, LGMN, SYNJ2, NHLRC3, GLB1, and RAB43 showed high predictive potential of unfavorable treatment outcome, while RPA2, SARNP, PCBP2, SF3B2, HNRNPF, RBBP4, MAGOHB, DUT, ERG28, and BUB3 were good predictive biomarkers of favorable treatment outcome. The identified proteins and related biological processes provide promising insights that could enhance the management and care of LARC patients.