SUVmax and metabolic tumor volume: surrogate image biomarkers of KRAS mutation status in colorectal cancer

KRAS mutation status between left- and right-sided colorectal cancer: are there any differences in computed tomography?

PURPOSE

To investigate the differences in clinicopathological and imaging features according to KRAS mutation status in left- and right-sided colorectal cancer.

METHOD

A total of 157 patients with pathologically proven colorectal cancer and preoperative contrast-enhanced multidetector CT examinations were enrolled. According to the tumor location and KRAS status, they were divided into two groups: the left-sided colorectal cancer (LCC) group (wild type, mutant type) and the right-sided colorectal cancer (RCC) group (wild type, mutant type). Clinicopathological and imaging features were recorded in each group. The imaging observation indicators included short axis diameter (SAD), longitudinal tumor length (LTL), tumor shape, pericolic fat stranding, bowel stenosis, intratumoral low-density range, enhancement pattern, and bowel obstruction. Univariate and multivariate logistic regression analyses were performed to compare the difference in KRAS mutation status between groups.

RESULTS

In the LCC group, SAD, tumor shape, degree of pericolic fat stranding, and bowel obstruction were significant indicators for predicting KRAS status (P < 0.05). In the RCC group, CA19-9, SAD, and intratumoral low-density range were significant indicators for predicting KRAS status (P < 0.05.). The area under the curve (AUC) of the combination image indicators in the LCC group was 0.802 [cutoff point 0.372, 95% confidence interval (CI) 0.718-0.888, sensitivity 85.4%, specificity 72.0%]. The AUC in the RCC group was 0.828 (cutoff point 0.647, 95% CI 0.726-0.931, sensitivity 79.5%, specificity 75.0%).

CONCLUSION

The CT imaging features associated with KRAS mutation status in the LCC and RCC groups were different. The combination of tumor location and imaging features can help to further improve the predictive value of KRAS status.

Predicting Kirsten Rat Sarcoma Virus Gene Mutation Status in Patients With Colorectal Cancer by Radiomics Models Based on Multiphasic CT

Objective

To develop and validate radiomics models based on multiphasic CT in predicting Kirsten rat sarcoma virus (KRAS) gene mutation status in patients with colorectal cancer (CRC).

Materials and Methods

A total of 231 patients with pathologically confirmed CRC were retrospectively enrolled and randomly divided into training(n=184) and test groups(n=47) in a ratio of 4:1. A total of 1316 quantitative radiomics features were extracted from non-contrast phase (NCP), arterial-phase (AP) and venous-phase (VP) CT for each patient. Four steps were applied for feature selection including Spearman correlation analysis, variance threshold, least absolute contraction and selection operator, and multivariate stepwise regression analysis. Clinical and pathological characteristics were also assessed. Subsequently, three classification methods, logistic regression (LR), support vector machine (SVM) and random tree (RT) algorithm, were applied to develop seven groups of prediction models (NCP, AP, VP, AP+VP, AP+VP+NCP, AP&amp;VP, AP&amp;VP&amp;NCP) for KRAS mutation prediction. The performance of these models was evaluated by receiver operating characteristics curve (ROC) analysis.

Results

Among the three groups of single-phase models, the AP model, developed by LR algorithm, showed the best prediction performance with an AUC value of 0.811 (95% CI:0.685–0.938) in the test cohort. Compared with the single-phase models, the dual-phase (AP+VP) model with the LR algorithm showed better prediction performance (AUC=0.826, 95% CI:0.700-0.952). The performance of multiphasic (AP+VP+NCP) model with the LR algorithm (AUC=0.811, 95%CI: 0.679-0.944) is comparable to the model with the SVM algorithm (AUC=0.811, 95%CI: 0.695-0.918) in the test cohort, but the sensitivity, specificity, and accuracy of the multiphasic (AP+VP+NCP) model with the LR algorithm were 0.810, 0.808, 0.809 respectively, which were highest among these seven groups of prediction models in the test cohort.

Conclusion

The CT radiomics models have the potential to predict KRAS mutation in patients with CRC; different phases may affect the predictive efficacy of radiomics model, of which arterial-phase CT is more informative. The combination of multiphasic CT images can further improve the performance of radiomics model.

The Molecular Associations of Signet-Ring Cell Carcinoma in Colorectum: Meta-Analysis and System Review

Background: Signet ring cell carcinoma (SC) accounts for 1% of total colorectal cancer (CRC) cases and is associated with aggressive behaviors, such as lymphatic invasion and distant metastases, resulting in poor prognosis. To date, there is still a lack of consensus on the genetic etiology underpinning this cancer subtype. This study aimed to clarify the molecular associations of SC by using meta-analysis and a systematic review. Methods: PubMed, Embase, and Cochrane Library were searched for studies evaluating the KRAS, BRAF, P53 statuses, and microsatellite instability (MSI) in CRC patients with different histological subtypes, including SC. The diagnosis of SC is defined as the signet ring cells comprising ≥50 percent of the tumor mass. By dividing the studies into subgroups based on the composition of control groups, such as classic adenocarcinoma (AC; no SC components) and non-SC (including those with SC components < 50%), the relative risk (RR) of molecular alterations for SC in each study were pooled using a random-effects model. Two reviewers identified trials for inclusion, assessed quality, and extracted data independently. Results: Data from 29 studies consisting of 9366 patients were included in this analysis. SC was associated positively with MSI (RR 1.78, 95% CI 1.34 to 2.37; 95% CI 0.77 to 4.15; p = 0.0005), BRAF mutation (RR 1.99, 95% CI 1.21 to 3.26; 95%CI 0.68 to 5.82; p = 0.0146), and negatively with KRAS mutation (RR 0.48, 95% CI 0.29 to 0.78; 95% CI 0.09 to 2.49; p = 0.0062). No association was found between SC and P53 expression (RR 0.92, 95% CI 0.76 to 1.13; 95%CI 0.61 to 1.39; p = 0.3790). Moreover, it was associated negatively with P53 gene mutations (RR 0.92, 95% CI 0.77 to 1.09; 95% CI 0.46 to 1.82; p = 0.1568), and P53 protein (RR 0.93, 95% CI 0.58 to 1.49; 95% CI 0.40 to 2.17; p = 0.6885). Conclusions: The molecular etiology of SC may be associated with the BRAF and MSI pathways. Its features, such as the high frequency of BRAF mutation, could partly explain its less favorable outcomes and limited effects of traditional chemotherapy.

Correlation between 18F-FDG PET/CT intra-tumor metabolic heterogeneity parameters and KRAS mutation in colorectal cancer

PURPOSE

The study aimed to evaluate the relationship between intra-tumor metabolic heterogeneity parameters of ¹⁸F-FDG and KRAS mutation status in colorectal cancer (CRC) patients and which threshold heterogeneity parameters could better reflect the heterogeneity characteristics of colorectal cancer.

METHODS

Medical data of 101 CRC patients who underwent ¹⁸F-FDG PET/CT and KRAS mutation analysis were selected. On PET scans, ¹⁸F-FDG traditional indices maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneity parameters coefficient of variation with a threshold of 2.5 (CV_2.5), CV_40%, heterogeneity index-1 (HI-1), and HI-2 of the primary lesions were obtained. We inferred correlations between these ¹⁸F-FDG parameters and KRAS mutation status.

RESULTS

41 patients (40.6%) had KRAS gene mutation. Assessment of FDG parameters showed that SUVmax (19.00 vs. 13.16, p < 0.001), MTV (11.64 vs. 8.83, p = 0.001), and TLG (102.85 vs. 69.76, p < 0.001), CV_2.5 (0.55 vs. 0.46, p = 0.006), and HI-2 (14.03 vs. 7.59, p < 0.001) of KRAS mutation were higher compared to wild-type (WT) KRAS. CV_40% (0.22 vs. 0.24, p = 0.001) was lower in the KRAS mutation group, while HI-1 had no significant difference between the two groups. Multivariate analysis showed that MTV (OR = 4.97, 1.04-23.83, p = 0.045) was the only significant predictor in KRAS mutation, using a cut-off of 7.62 (AUC = 0.695), and MTV showed a sensitivity of 90.2% and specificity of 45.0%. However, the PET parameters were not independent predictors in KRAS mutation.

CONCLUSION

KRAS gene mutant CRC patients had more ¹⁸F-FDG uptake (SUVmax, MTV, TLG) and heterogeneity (CV_2.5, HI-2) than WT KRAS. MTV was the only independent predictor of KRAS gene mutation in colorectal cancer patients.

Clinical Significance and Prognostic Value of the Maximum Standardized Uptake Value of 18F-Flurodeoxyglucose Positron Emission Tomography-Computed Tomography in Colorectal Cancer

Background

The role of ¹⁸F-flurodeoxyglucose (¹⁸F-FDG) positron emission tomography–computed tomography (PET/CT) in colorectal cancer (CRC) remains unclear. This study aimed to explore the association of the maximum standardized uptake value (SUVmax), a parameter of ¹⁸F-FDG PET/CT, with KRAS mutation, the Ki-67 index, and survival in patients with CRC.

Methods

Data of 66 patients with CRC who underwent ¹⁸F-FDG PET/CT was retrospectively collected in our center. The clinical significance of the SUVmax in CRC and the association of the SUVmax with KRAS mutation and the Ki-67 index were determined. A meta-analysis was conducted by a systematic search of PubMed, Web of Science, and CNKI databases, and the data from published articles were combined with that of our study. The association of the SUVmax with KRAS mutation and the Ki-67 index was determined using the odds ratio to estimate the pooled results. The hazard ratio was used to quantitatively evaluate the prognosis of the SUVmax in CRC.

Results

By analyzing the data of 66 patients with CRC, the SUVmax was found not to be related to the tumor-node-metastasis stage, clinical stage, sex, and KRAS mutation but was related to the tumor location and nerve invasion. The SUVmax had no significant correlation with the tumor biomarkers and the Ki-67 index. Data of 17 studies indicated that the SUVmax was significantly increased in the mutated type compared with the wild type of KRAS in CRC; four studies showed that there was no remarkable difference between patients with a high and low Ki-67 index score regarding the SUVmax. Twelve studies revealed that the SUVmax had no significant association with overall survival and disease-free survival in CRC patients.

Conclusions

Based on the combined data, this study demonstrated that the SUVmax of ¹⁸F-FDG PET/CT was different between colon and rectal cancers and associated with KRAS mutation but not the Ki-67 index; there was no significant association between the SUVmax and survival of patients with CRC.

Pretreatment 18F-FDG PET/CT Imaging Predicts the KRAS/NRAS/BRAF Gene Mutational Status in Colorectal Cancer

Objective

To investigate the association between KRAS/NRAS/BRAF mutations and metabolic parameters of pretreatment ¹⁸F-FDG PET/CT in colorectal cancer (CRC).

Methods

A total of 85 patients with CRC were included in the study. PET/CT was performed in all the patients before surgery. The histopathological examination and analysis of the gene mutational status of the primary tumor were conducted. The associations among clinical features, PET metabolic parameters, and the gene mutational status were investigated. Moreover, receiver operating characteristic (ROC) curves for maximum standard uptake value (SUVmax) of the primary tumor were generated along with analysis of the target tissue to nontarget tissue ratio (T/NT) for predicting the efficacy of KRAS/NRAS/BRAF mutations in CRC. Finally, the corresponding area under the curve, the optimal cutoff value, and the corresponding sensitivity and specificity were obtained.

Results

The mutation rate of KRAS/NRAS/BRAF was 54.12% (46/85). In addition, both SUVmax and T/NT were significantly higher in the KRAS/NRAS/BRAF-mutation groups compared to the wild-type group (15.88 ± 6.71 vs. 12.59 ± 5.79, 8.04 ± 3.03 vs. 6.38 ± 2.80; P=0.012 and 0.004, respectively). Results from the ROC curve also showed that the cutoff values for T/NT and SUVmax were 5.14 and 12.40, respectively, while the predictive accuracy was 0.682 and 0.647, respectively. On the other hand, the sensitivity was 91.30% and 65.22% while the specificity was 43.59% and 64.10%, respectively. Moreover, univariate analysis showed that the KRAS/NRAS/BRAF mutation was not significantly associated with gender, age, lesion location, tumor length, pathological type, tissue differentiation, and UICC staging (all P > 0.05).

Conclusion

T/NT ratio and SUVmax could be the potential surrogate imaging indicators to predict the KRAS/NRAS/BRAF mutational status in CRC patients.

MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients

Background and Purpose

Locally advanced rectal cancer (LARC) is a heterogeneous disease with little information about KRAS status and image features. The purpose of this study was to analyze the association between T2 magnetic resonance imaging (MRI) radiomics features and KRAS status in LARC patients.

Material and Methods

Eighty-three patients with KRAS status information and T2 MRI images between 2012.05 and 2019.09 were included. Least absolute shrinkage and selection operator (LASSO) regression was performed to assess the associations between features and gene status. The patients were divided 7:3 into training and validation sets. The C-index and the average area under the receiver operator characteristic curve (AUC) were used for performance evaluation.

Results

The clinical characteristics of 83 patients in the KRAS mutant and wild-type cohorts were balanced. Forty-two (50.6%) patients had KRAS mutations, and 41 (49.4%) patients had wild-type KRAS. A total of 253 radiomics features were extracted from the T2-MRI images of LARC patients. One radiomic feature named X.LL_scaled_std, a standard deviation value of scaled wavelet-transformed low-pass channel filter, was selected from 253 features (P=0.019). The radiomics-based C-index values were 0.801 (95% CI: 0.772-0.830) and 0.703 (95% CI: 0.620-0.786) in the training and validation sets, respectively.

Conclusion

Radiomics features could differentiate KRAS status in LARC patients based on T2-MRI images. Further validation in a larger dataset is necessary in the future.

Clinical application and research advancement of positron emission tomography/computed tomography in colorectal cancer

Colorectal cancer is one of the most common malignant tumors of the digestive system. Early diagnosis and accurate staging and restaging of tumors are the preconditions for standardized treatment of colorectal cancer, which is conducive to the selection of treatment options and the evaluation of prognosis, as well as the improvement of patients' quality of life. With the popularization of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT), its value in the diagnosis, staging and restaging, treatment decision-making, and efficacy and prognosis assessment of colorectal cancer is becoming increasingly important. This review briefly introduces the application and advancement of PET/CT in the diagnosis and treatment of colorectal cancer, in the hope that clinicians can have a more comprehensive understanding of the significance of PET/CT in the diagnosis and treatment of colorectal cancer.

Positive Correlation Between Somatic Mutations in RAS Gene and Colorectal Cancer in Telangana Population: Hospital-Based Study in a Cosmopolitan City

Colorectal cancer (CRC) ranks among the most prevalent cancer types in both men and women. Screening of RAS (Kirsten rat sarcoma viral oncogene homolog (KRAS), neuro-blastoma RAS viral oncogene homolog (NRAS), and v-raf murine sarcoma viral oncogene homolog B1 (BRAF)) somatic mutations is necessary prior to considering anti-epidermal growth factor receptor (EGFR) therapies in CRC patients. Next-generation sequencing studies have confirmed that RAS gene panels could be used while developing treatment strategies for patients with CRC. The present study explored genetic mutations in KRAS, NRAS, and BRAF in CRC patients in the Telangana state of India. Patients with confirmed CRC (n = 100) who visited the Apollo hospitals were evaluated. Genomic DNA was extracted from formalin-fixed, paraffin-embedded tissues, and pyrosequencing analysis was performed. Patient DNA samples were screened for 54 different KRAS, NRAS, and BRAF mutations, which revealed 34 somatic mutations. Exon 11 of BRAF possessed 4 mutations with highest individuals documented with G469A mutation. Pyrosequencing, a reliable method for analyzing somatic mutations present in RAS, could aid in taking treatment decisions for patients with CRC.