Comparative Analysis of Circulating Biomarkers for Patients Undergoing Resection of Colorectal Liver Metastases

C-reactive protein and digestive pathologies: A narrative review for daily clinical use

The aim of this narrative review is to familiarize clinicians, especially digestive surgeons, to adequately use of serum C-reactive protein as a reliable noninvasive biomarker in diverse practical clinical situations. We hope that the review will help clinicians for their decision-making when facing various digestive diseases including operative and nonoperative pathologies such as anastomotic leakage, pancreatitis, emergency situation, and digestive cancer management and prognosis.

Utility and specificity of plasma heat shock protein 90 alpha, CEA, and CA199 as the diagnostic test in colorectal cancer liver metastasis

BACKGROUND

Plasma heat shock protein 90 alpha (Hsp90α) has been suggested as a novel biomarker for the diagnosis and prognosis of cancer. Carcinoembryonic antigen (CEA) and carbohydrate antigen199 (CA199) are traditional tumor biomarkers for colorectal cancer (CRC). Previous studies have shown that Hsp90α and the combination of Hsp90α and CEA are optimal biomarkers for CRC at an early stage. However, research on the use of Hsp90α alone or in combination with CEA and/or CA199 in diagnosing CRC development, particularly liver metastasis, is limited. This study sought to investigate the value of Hsp90α alone or in combination with CEA/CA199 in diagnosing CRC liver metastasis.

METHODS

The clinical data of 472 CRC patients were retrospectively analyzed, which were confirmed by clinical manifestations and a histopathological examination associated with an imaging diagnosis. The levels of Hsp90α, and CEA, and CA199 were assessed by enzyme-linked immunoassays and electrochemiluminescence immunoassays. Liver metastasis was diagnosed by imaging or pathology of the liver. Logistic regression models were used to analyze associations between Hsp90α, CEA, and CA199, and liver metastasis in CRC. The areas under the curves (AUCs) were used to compare the utility of Hsp90α, CEA, and CA199 in the diagnosis of CRC liver metastasis (CRLM). Additionally, we compared the diagnostic utility of the models, including the Hsp90α plus 1 of the other serum markers, and a combination of the 3 serum makers.

RESULTS

The plasma levels of Hsp90α, CEA, and CA199 were positively associated with a higher risk of CRLM [odds ratios (OR) ranging from 1.36-2.72]. The AUCs of CEA, CA199, and Hsp90α for CRLM were 0.80, 0.69, and 0.55, respectively. The AUCs for the combination of Hsp90α and CEA, combination of Hsp90α and CA199, combinations of Hsp90α, CEA, and CA199 were 0.75, 0.66, 0.76, respectively. The combination of Hsp90α, CEA, and CA199 did not improve the diagnostic utility for liver metastasis in CRC.

CONCLUSIONS

The level of Hsp90α was elevated in CRC and was associated with CRLM. Thus, the Hsp90α is a potential biomarker for CRLM. CEA has the largest diagnostic utility for CRLM. Adding Hsp90α to CEA/CA199 did not improve their diagnostic utility for CRLM.

Circulating cell-free circRNA panel predicted tumorigenesis and development of colorectal cancer

Background

Colorectal cancer (CRC) is reported with high morbidity and mortality. Currently, the sensitivity of diagnostic markers for colorectal cancer is low. Therefore, further exploration of new plasma diagnostic markers for early detection of colorectal cancer is of great value. We aimed to explore potential circRNAs in plasma as biomarkers for early diagnosis of CRC.

Methods

We employed the circRNA microarray to investigate dysregulated circRNAs in plasma samples of CRC patients, colorectal adenoma patients (CRA), and healthy controls. Through in‐depth analysis, significantly differentially expressed circRNAs were screened as candidate targets.

Results

Eight circRNAs (hsa_circ_104885, hsa_circ_100185, hsa_circ_103171, hsa_circ_001978, hsa_circ_105039, hsa_circ_103627, hsa_circ_101717, and hsa_circ_104192) were obtained as candidate circRNAs with upregulation in CRC comparing with both CRA and healthy control. Through detecting the plasma expression levels of eight candidate targets, we identified three circRNA (hsa_circ_001978, hsa_circ_105039, and hsa_circ_103627) with increased level which were consistent with the microarray results in training set. Further validation found the circRNA panel was consistent with training set. The ROC curve also revealed a high diagnostic ability of hsa_circ_001978, hsa_circ_105039, and hsa_circ_103627 in predicted the CRC from CRA patients (AUC = 0.966) as well as healthy controls (AUC = 0.969).

Conclusion

Our data suggest that hsa_circ_001978, hsa_circ_105039, and hsa_circ_103627 might be a CRC‐specific biomarker for early diagnosis.

Predicting Survival for Hepatic Arterial Infusion Chemotherapy of Unresectable Colorectal Liver Metastases: Radiomics Analysis of Pretreatment Computed Tomography

OBJECTIVE

Hepatic arterial infusion chemotherapy (HAIC) is an effective treatment for advanced unresectable colorectal cancer liver metastases (CRLM). This study was conducted to predict the efficacy of HAIC in patients with unresectable CRLM by radiomics methods based on pretreatment computed tomography (CT) examinations and clinical data.

MATERIALS AND METHODS

A total of 63 patients were included in this study (41 in the training group and 22 in the validation group). All these patients underwent CT examination before HAIC. During the follow-up period, CT scans and laboratory examinations were performed regularly. Eighty-five radiological features were extracted from the regions of interest (ROIs) of CT images using the PyRadiomics program. The t-test and correlation were applied to select features. These features were analyzed using LASSO-Cox regression, and a linear model was developed to predict overall survival (OS).

RESULTS

After reducing features by t-test and correlation test, seven features remained. After LASSO-Cox cross-validation, four features remained at λ = 0.232. They were gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), neighborhood gray tone difference matrix (NGTDM), and the location of the primary tumor. The C-index was 0.758 in the training group and 0.743 in the test group. Nomograms predicting 1-, 2-, and 3-year survival were established.

CONCLUSION

Our study demonstrates that a radiomics approach based on pretreatment CT texture analysis has the ability to predict early the outcome of HAIC in patients with advanced unresectable colorectal cancer with a high degree of accuracy and feasibility.