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.

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.

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.

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

Introduction: The standard treatment for locally advanced rectal cancer (LARC) is neoadjuvant chemoradiotherapy (nCRT). To select patients who would benefit the most from nCRT, there is a need for predictive biomarkers. The aim of this study was to evaluate the role of clinical, pathological, radiological, inflammation-related genetic, and hematological parameters in the prediction of post-nCRT response. Materials and methods: In silico analysis of published transcriptomics datasets was conducted to identify candidate genes, whose expression will be measured using quantitative Real Time PCR (qRT-PCR) in pretreatment formaline-fixed paraffin-embedded (FFPE) samples. In this study, 75 patients with LARC were prospectively included between June 2020-January 2022. Patients were assessed for tumor response in week 8 post-nCRT with pelvic MRI scan and rigid proctoscopy. For patients with a clinical complete response (cCR) and initially distant located tumor no immediate surgery was suggested ("watch and wait" approach). The response after surgery was assessed using histopathological tumor regression grading (TRG) categories from postoperative specimens by Mandard. Responders (R) were defined as patients with cCR without operative treatment, and those with TRG 1 and TRG 2 postoperative categories. Non-responders (NR) were patients classified as TRG 3-5. Results: Responders group comprised 35 patients (46.6%) and NR group 53.4% of patients. Analysis of published transcriptomics data identified genes that could predict response to treatment and their significance was assessed in our cohort by qRT-PCR. When comparison was made in the subgroup of patients who were operated (TRG1 vs. TRG4), the expression of IDO1 was significantly deregulated (p < 0.05). Among hematological parameters between R and NR a significant difference in the response was detected for neutrophil-to-monocyte ratio (NMR), initial basophil, eosinophil and monocyte counts (p < 0.01). According to MRI findings, non-responders more often presented with extramural vascular invasion (p < 0.05). Conclusion: Based on logistic regression model, factors associated with favorable response to nCRT were tumor morphology and hematological parameters which can be easily and routinely derived from initial laboratory results (NMR, eosinophil, basophil and monocyte counts) in a minimally invasive manner. Using various metrics, an aggregated score of the initial eosinophil, basophil, and monocyte counts demonstrated the best predictive performance.

Evaluation of Clinical and Genetic Determinants of Treatment OutCome In EGFR Mutation Positive Advanced Lung Adenocarcinoma.

Background: The aim of this research was to evaluate clinical and low-cost genetic determinants of treatment outcome in EGFR mutation positive advanced lung adenocarcinoma patients. Material and Methods: EGFR mutation testing and EGFR 181946C>T genotyping were performed in 101 advanced lung adenocarcinoma patients using qRT-PCR and PCR-RFLP, respectively. Progression-free survival was defined as the time from the start of TKI therapy to date of progression, and overall survival as the time from diagnosis to death from any cause. Pain level was evaluated using a Numerical Rating Scale and the Verbal Descriptor Scale. Statistical significance was considered for P < .05. Results: Patients were treated with EGFR-TKIs for a period of 1-39months (median 9), with a median PFS of 12.0 months (10.4-13.6, CI 95%), and a median OS of 19.0 months (15.1-22.7, CI 95%). The presence of pain was significantly correlated with the existence of bone (P < .001) and adrenal glands metastases (P = .029). Genetic factors did not have a direct impact on pain management but had a significant effect on the response to TKIs leading to pain alleviation. Conclusions: EGFR mutation subtype and the EGFR 181946 C>T SNP had a significant effect on the response to TKI inducing an indirect anti-dolorous effect.

Comparison of Different Machine Learning Models in Prediction of Postirradiation Recurrence in Prostate Carcinoma Patients.

After primary treatment of localized prostate carcinoma (PC), up to a third of patients have disease recurrence. Different predictive models have already been used either for initial stratification of PC patients or to predict disease recurrence. Recently, artificial intelligence has been introduced in the diagnosis and management of PC with a potential to revolutionize this field. The aim of this study was to analyze machine learning (ML) classifiers in order to predict disease progression in the moment of prostate-specific antigen (PSA) elevation during follow-up. The study cohort consisted of 109 PC patients treated with external beam radiotherapy alone or in combination with androgen deprivation therapy. We developed and evaluated the performance of two ML algorithms based on artificial neural networks (ANN) and naïve Bayes (NB). Of all patients, 72.5% was randomly selected for a training set while the remaining patients were used for testing of the models. The presence/absence of disease progression was defined as the output variable. The input variables for models were conducted from the univariate analysis preformed among two groups of patients in the training set. They included two pretreatment variables (UICC stage and Gleason's score risk group) and five posttreatment variables (nadir PSA, time to nadir PSA, PSA doubling time, PSA velocity, and PSA in the moment of disease reevaluation). The area under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, and predictive accuracy was calculated to test the models' performance. The results showed that specificity was similar for both models, while NB achieved better sensitivity then ANN (100.0% versus 94.4%). The ANN showed an accuracy of 93.3%, and the matching for NB model was 96.7%. In this study, ML classifiers have shown potential for application in routine clinical practice during follow-up when disease progression was suspected.

Hematological parameters in EGFR-mutated advanced NSCLC patients treated with TKIs: predicting survival and toxicity.

Background: The aim of this study was to analyze the prognostic value of pre-treatment hematological parameters in EGFR-mutated non-small cell lung cancer patients treated with tyrosine-kinase inhibitors (TKIs).Patients and methods: Patients with EGFR mutations were treated with EGFR-TKIs in the first line until progression/unacceptable toxicity. Hematological parameters were derived from the absolute baseline differential counts of a complete blood count. The associations between the patients' and tumor characteristics were analyzed using Pearson Chi-Square, Fisher's exact, t-test, and Mann-Whitney tests. Cutoff values were determined using ROC curves, and correlation with survival was examined by Kaplan-Meier method and Cox regression.Results: Patients with NMR<12.62 had a longer PFS compared to patients with higher NMR values (12.0 vs. 10.0 months, p = 0.054) and a significantly longer OS (20.0 vs. 11.0 months, p = 0.010). The same parameter was confirmed as a predictors of favorable response in the patient subgroup with activating EGFR mutations. Patients with NLR>2.9 and LMR<2.5 more often presented with paronichia and diarrhea, and patients with PLR>190 more often had paronichia, diarrhea and hyperbilirubinemia.Conclusion: Low baseline value of the hematological parameter NMR has shown potential as a routine, low-cost, and minimally invasive predictor of survival in EGFR-TKI-treated NSCLC patients.

The role of haematological parameters in predicting the response to radical chemoradiotherapy in patients with anal squamous cell cancer.

BACKGROUND: Historically, the treatment of choice for anal cancer had been abdominoperineal resection (APR). Radical radiotherapy with concurrent 5-fluorouracil plus mitomycin C chemotherapy was later established as standard therapy, although with a failure rate of 20-30%. The aim of this study was to evaluate the outcomes after radical chemoradiotherapy (CRT), prognostic and predictive factors and patterns of failure. PATIENTS AND METHODS: This study included 47 patients treated with radical CRT for patohistologicaly confirmed anal squamous cell carcinoma. Analysed haematological parameters included: neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and haemoglobin level. The final logistic regression model included treatment break period. Tumour response was assessed at 24 weeks from CRT completion. Follow-up was performed every 3 months during the first two years, and every 6 months thereafter. RESULTS: A complete clinical response (CR) was detected in 30 patients (63.8%). Patients who did not achieve a 6-months CR and those who had a CR after 6 months but then relapsed were referred to surgical treatment. With combined CRT and surgical salvage treatment the CR rate was 80.9%. Patients with CR after 6 months had significantly longer disease-free survival (DFS), progression-free survival (PFS), and overall survival (OS). A significant effect on the 6-month response was confirmed for PLR (p = 0.03). CONCLUSIONS: Important prognostic factors associated with CR were baseline haemoglobin level and period of treatment interruptions. Potential haematological prognostic factors could be PLR and NLR, which can be routinely determined by low-cost and minimally invasive methods.