Survival Impact of Primary Tumor Lymph Node Status and Circulating Tumor Cells in Patients with Colorectal Liver Metastases

Multifactorial risk prediction analysis of liver metastasis in colorectal cancer: incorporating programmed cell death ligand 1 combined positive score and other factors

BACKGROUND

The occurrence of liver metastasis significantly affects the prognosis of colorectal cancer (CRC). Existing research indicates that primary tumor location, vascular invasion, lymph node metastasis, and abnormal preoperative tumor markers are risk factors for CRC liver metastasis. Positive expression of programmed cell death ligand 1 (PD-L1) may serve as a favorable prognostic marker for nasopharyngeal and gastric cancers, in which combined positive score (CPS) quantifies the level of PD-L1 expression. This study aimed to explore CPS as a potential risk factor for CRC liver metastasis and integrate other independent risk factors to establish a novel predictive model for CRC liver metastasis.

METHODS

A retrospective analysis was conducted on 437 patients with CRC pathologically diagnosed at The Second Xiangya Hospital of Central South University from January 1, 2019, to December 31, 2021. Data were collected, including CPS, age, gender (male and female), primary tumor location, Ki-67 expression, pathologic differentiation, neural invasion, vascular invasion, lymph node metastasis, and preoperative tumor markers. The optimal cutoff point for the continuous variable CPS was determined using the Youden index, and all CPSs were dichotomized into high- and low-risk groups based on this threshold (scores below the threshold were considered high risk, and score above the threshold were considered low risk). Univariate logistic regression analysis was employed to identify risk factors for CRC liver metastasis, followed by multivariate logistic regression analysis to integrate the selected risk factors. The predictive model was validated through the construction of receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). A nomogram was constructed for visualization.

RESULTS

The determined cutoff point for PD-L1 CPS was 4.5, with scores below this threshold indicating a high risk of CRC liver metastasis. In addition, primary tumor origin other than the rectum, presence of pericolonic lymph node metastasis, and abnormal levels of tumor markers carcinoembryonic antigen and cancer antigen 19-9 were identified as independent risk factors for CRC liver metastasis. The constructed clinical prediction model demonstrated good predictive ability and accuracy, with an area under the ROC curve of 0.871 (95% CI, 0.838-0.904).

CONCLUSION

The exploration and validation of CPS as a novel predictor of CRC liver metastasis were performed. Based on these findings, a new clinical prediction model for CRC liver metastasis was developed by integrating other independent risk factors. The DCA, clinical impact curve, and nomogram graph constructed on the basis of this model have significant clinical implications and guide clinical practice.

Constructing a prognostic model for colorectal cancer with synchronous liver metastases after preoperative chemotherapy: a study based on SEER and an external validation cohort

BACKGROUND

The combination of preoperative chemotherapy and surgical treatment has been shown to significantly enhance the prognosis of colorectal cancer with liver metastases (CRLM) patients. Nevertheless, as a result of variations in clinicopathological parameters, the prognosis of this particular group of patients differs considerably. This study aimed to develop and evaluate Cox proportional risk regression model and competing risk regression model using two patient cohorts. The goal was to provide a more precise and personalized prognostic evaluation system.

METHODS

We collected information on individuals who had a pathological diagnosis of colorectal cancer between 2000 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) Database. We obtained data from patients who underwent pathological diagnosis of colorectal cancer and got comprehensive therapy at the hospital between January 1, 2010, and June 1, 2022. The SEER data collected after screening according to the inclusion and exclusion criteria were separated into two cohorts: a training cohort (training cohort) and an internal validation cohort (internal validation cohort), using a random 1:1 split. Subgroup Kaplan-Meier (K-M) survival analyses were conducted on each of the three groups. The data that received following screening from the hospital were designated as the external validation cohort. The subsequent variables were chosen for additional examination: age, gender, marital status, race, tumor site, pretreatment carcinoembryonic antigen level, tumor size, T stage, N stage, pathological grade, number of tumor deposits, perineural invasion, number of regional lymph nodes examined, and number of positive regional lymph nodes. The primary endpoint was median overall survival (mOS). In the training cohort, we conducted univariate Cox regression analysis and utilized a stepwise regression approach, employing the Akaike information criterion (AIC) to select variables and create Cox proportional risk regression models. We evaluated the accuracy of the model using calibration curve, receiver operating characteristic curve (ROC), and area under curve (AUC). The effectiveness of the models was assessed using decision curve analysis (DCA). To evaluate the non-cancer-related outcomes, we analyzed variables that had significant impacts using subgroup cumulative incidence function (CIF) and Gray's test. These analyses were used to create competing risk regression models. Nomograms of the two models were constructed separately and prognostic predictions were made for the same patients in SEER database.

RESULTS

This study comprised a total of 735 individuals. The mOS of the training cohort, internal validation cohort, and QDU cohort was 55.00 months (95%CI 46.97-63.03), 48.00 months (95%CI 40.65-55.35), and 68.00 months (95%CI 54.91-81.08), respectively. The multivariate Cox regression analysis revealed that age, N stage, presence of perineural infiltration, number of tumor deposits and number of positive regional lymph nodes were identified as independent prognostic risk variables (p < 0.05). In comparison to the conventional TNM staging model, the Cox proportional risk regression model exhibited a higher C-index. After controlling for competing risk events, age, N stage, presence of perineural infiltration, number of tumor deposits, number of regional lymph nodes examined, and number of positive regional lymph nodes were independent predictors of the risk of cancer-specific mortality (p < 0.05).

CONCLUSION

We have developed a prognostic model to predict the survival of patients with synchronous CRLM who undergo preoperative chemotherapy and surgery. This model has been tested internally and externally, confirming its accuracy and reliability.

Importance of resection margin after resection of colorectal liver metastases in the era of modern chemotherapy: population-based cohort study

BACKGROUND

Resection margin has been associated with overall survival following liver resection for colorectal liver metastasis. The aim of this study was to examine how resection margins of 0.0 mm, 0.1-0.9 mm and ≥1 mm influence overall survival in patients resected for colorectal liver metastasis in a time of modern perioperative chemotherapy and surgery.

METHODS

Using data from the national registries Swedish Colorectal Cancer Registry and Swedish National Quality Registry for Liver, Bile Duct and Gallbladder Cancer, patients that had liver resections for colorectal liver metastasis between 2009 and 2013 were included. In patients with a narrow or unknown surgical margin the original pathological reports were re-reviewed. Factors influencing overall survival were analysed using a Cox proportional hazard model.

RESULTS

A total of 754 patients had a known margin status, of which 133 (17.6%) patients had a resection margin <1 mm. The overall survival in patients with a margin of 0 mm or 0.1-0.9 mm was 42 (95% c.i. 31 to 53) and 48 (95% c.i. 35 to 62) months respectively, compared with 75 (95% c.i. 65 to 85) for patients with ≥1 mm margin, P < 0.001. Margins of 0 mm or 0.1-0.9 mm were associated with poor overall survival in the multivariable analysis, HR 1.413 (95% c.i. 1.030 to 1.939), P = 0.032, and 1.399 (95% c.i. 1.025 to 1.910), P = 0.034, respectively.

CONCLUSIONS

Despite modern chemotherapy the resection margin is still an important factor for the survival of patients resected for colorectal liver metastasis, and a margin of ≥1 mm is needed to achieve the best possible outcome.

Recurrence-risk stratification using the Beppu score and selection of perioperative chemotherapy for colorectal liver metastases

The annual postoperative disease-free survival for colorectal liver metastases can be easily estimated by weighting six preoperative clinical parameters (Beppu score). We identified three recurrence-risk stratification groups: the low (≤6 points), moderate (7-10 points), and high-risk (≥11 points). For low-, moderate-, and high-risk patients, hepatectomy alone, hepatectomy with adjuvant chemotherapy, and hepatectomy with preoperative chemotherapy are recommended, respectively. The Beppu score enables the decision on the necessity and timing of perioperative chemotherapy.

Prognostic value of circulating tumor cells in patients with recurrent and metastatic colorectal cancer: a systematic review and meta-analysis

BACKGROUND

The detection of circulating tumor cells (CTCs) has been employed in prognosticating the likelihood of recurrence and metastasis in colorectal cancer (CRC). Nonetheless, the findings remain enigmatic. This meta-analysis aims to systematically assess the predictive utility of CTCs detection in postoperative recurrence and metastasis among CRC patients.

METHODS

A comprehensive search of PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), and Cochrane Library was conducted from inception to March 2023. Pooled estimates including sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and summary receiver operating characteristic curve were computed to gauge the predictive value. The QUADAS-2 tool was employed to appraise bias risks in individual studies. The assessment of publication bias in the included literature was performed using Deek's funnel plot.

RESULTS

The study encompassed 16 articles and 2037 patients. After synthesizing the pertinent indices, CTCs monitoring demonstrated sensitivity and specificity of 0.71 (95% confidence interval [CI], 0.62-0.79) and 0.71 (95% CI, 0.55-0.83), respectively. The corresponding values for positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 2.4 (95% CI, 1.5-4.0), 0.41 (95% CI, 0.29-0.58), and 6 (95% CI, 3-13). The summary receiver operating characteristic curve yielded an area under the curve of 0.76 (95% CI, 0.72-0.80). Deek's funnel plot analysis revealed no significant evidence of publication bias (P = .42).

CONCLUSION

This investigation underscores the potential of CTCs detection as a noninvasive modality to efficaciously prognosticate postoperative recurrence and metastasis in CRC.

A machine learning model for colorectal liver metastasis post-hepatectomy prognostications

Background

Currently, surgical resection is the mainstay for colorectal liver metastases (CRLM) management and the only potentially curative treatment modality. Prognostication tools can support patient selection for surgical resection to maximize therapeutic benefit. This study aimed to develop a survival prediction model using machine learning based on a multicenter patient sample in Hong Kong.

Methods

Patients who underwent hepatectomy for CRLM between 1 January 2009 and 31 December 2018 in four hospitals in Hong Kong were included in the study. Survival analysis was performed using Cox proportional hazards (CPH). A stepwise selection on Cox multivariable models with Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to a multiply-imputed dataset to build a prediction model. The model was validated in the validation set, and its performance was compared with that of Fong Clinical Risk Score (CRS) using concordance index.

Results

A total of 572 patients were included with a median follow-up of 3.6 years. The full models for overall survival (OS) and recurrence-free survival (RFS) consist of the same 8 established and novel variables, namely colorectal cancer nodal stage, CRLM neoadjuvant treatment, Charlson Comorbidity Score, pre-hepatectomy bilirubin and carcinoembryonic antigen (CEA) levels, CRLM largest tumor diameter, extrahepatic metastasis detected on positron emission-tomography (PET)-scan as well as KRAS status. Our CRLM Machine-learning Algorithm Prognostication model (CMAP) demonstrated better ability to predict OS (C-index =0.651), compared with the Fong CRS for 1-year (C-index =0.571) and 5-year OS (C-index =0.574). It also achieved a C-index of 0.651 for RFS.

Conclusions

We present a promising machine learning algorithm to individualize prognostications for patients following resection of CRLM with good discriminative ability.

Which patients are prone to suffer liver metastasis? A review of risk factors of metachronous liver metastasis of colorectal cancer

Background

In recent years, with the increasing incidence of colorectal cancer (CRC) and its high fatality rate, CRC has seized the attention of the world. And liver metastasis, as the main cause of death of CRC, has become the leading cause of treatment failure in CRC, especially metachronous liver metastasis, have caused patients who underwent bowel resection to experience multiple tortures.

Main body

Metachronous liver metastasis has severely affected the quality of life and prognosis of patients. Therefore, in this review, we discuss risk factors for metachronous liver metastasis of CRC, which is the premise for effective intervention for CRC patients who suffer metachronous liver metastasis after undergoing surgery, as well as the signaling pathways associated with CRC.

Conclusion

The occurrence of metachronous liver metastasis is closely related to histology-based prognostic biomarkers, serum-based biomarkers, tumor microenvironment, pre-metastatic niche, liquid biopsy and tissue-based biomarkers. Further research is required to explore the risk factors associated with liver metastasis of CRC.

Predicting metachronous liver metastasis in patients with colorectal cancer: development and assessment of a new nomogram

Background

We aimed to develop and validate a nomogram model, which could predict metachronous liver metastasis in colorectal cancer within two years after diagnosis.

Methods

A retrospective study was performed on colorectal cancer patients who were admitted to Beijing Shijitan Hospital from January 1, 2016 to June 30, 2019. The least absolute shrinkage and selection operator (LASSO) regression model was used to optimize feature selection for susceptibility to metachronous liver metastasis in colorectal cancer. Multivariable logistic regression analysis was applied to establish a predictive model through incorporating features selected in the LASSO regression model. C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were employed to assess discrimination, distinctiveness, consistency with actual occurrence risk, and clinical utility of candidate predictive model. Internal validation was assessed with bootstrapping method.

Results

Predictors contained in candidate prediction nomogram included age, CEA, vascular invasion, T stage, N stage, family history of cancer, and KRAS mutation. This model displayed good discrimination with a C-index of 0.787 (95% confidence interval: 0.728–0.846) and good calibration, whereas area under the ROC curve (AUC) of 0.786. Internal validation obtained C-index of 0.786, and AUC of validation cohort is 0.784. Based on DCA, with threshold probability range from 1 to 60%; this predictive model might identify colorectal cancer metachronous liver metastasis to achieve a net clinical benefit.

Conclusion

We have developed and validated a prognostic nomogram with good discriminative and high accuracy to predict metachronous liver metastasis in CRC patients.

CEA, CA19-9, circulating DNA and circulating tumour cell kinetics in patients treated for metastatic colorectal cancer (mCRC)

BACKGROUND

We previously reported that CEA kinetics are a marker of progressive disease (PD) in metastatic colorectal cancer (mCRC). This study was specifically designed to confirm CEA kinetics for predicting PD and to evaluate CA19-9, cell-free DNA (cfDNA), circulating tumour DNA (ctDNA) and circulating tumour cell (CTC) kinetics.

METHODS

Patients starting a chemotherapy (CT) with pre-treatment CEA > 5 ng/mL and/or CA19.9 > 30 UI/mL were prospectively included. Samples were collected from baseline to cycle 4 for CEA and CA19-9 and at baseline and the sixth week for other markers. CEA kinetics were calculated from the first to the third or fourth CT cycle.

RESULTS

A total of 192 mCRC patients were included. CEA kinetics based on the previously identified >0.05 threshold was significantly associated with PD (p < 0.0001). By dichotomising by the median value, cfDNA, ctDNA and CA19-9 were associated with PD, PFS and OS in multivariate analysis. A circulating scoring system (CSS) combining CEA kinetics and baseline CA19-9 and cfDNA values classified patients based on high (n = 58) and low risk (n = 113) of PD and was independently associated with PD (ORa = 4.6, p < 0.0001), PFS (HRa = 2.07, p < 0.0001) and OS (HRa = 2.55, p < 0.0001).

CONCLUSIONS

CEA kinetics alone or combined with baseline CA19-9 and cfDNA are clinically relevant for predicting outcomes in mCRC.

TRIAL REGISTRATION NUMBER

NCT01212510.

Surgery for Colorectal Cancer: A Trigger for Liver Metastases Development? New Insights into the Underlying Mechanisms

Surgery is a crucial intervention and provides the best chance of cure for patients with colorectal cancer. Experimental and clinical evidence, however, suggests that paradoxically surgery itself may precipitate or accelerate tumor recurrence and/or liver metastasis development. This review addresses the various aspects of surgery-induced metastasis formation and sheds light on the role of inflammation as potential trigger for metastasis development. Understanding these mechanisms may provide potential new perioperative interventions to improve treatment outcomes, and as such could transform the perioperative timeframe from a facilitator of metastatic progression to a window of opportunity to reduce the risk of liver metastasis development. Ultimately, this can potentially improve long-term survival rates and quality of life in patients with colorectal cancer.

Assessment of circulating tumor cells in peripheral blood using flow cytometry in patients with surgery for colorectal cancer – review

Introduction: Colorectal cancer (CRC) is the third most common neoplasia in the world. Circulating tumor cells (CTC) have a prognostic value and can be useful in monitoring solid neoplasia. Only one method for CTC identification has received the approval and this is the CellSearch® system based on the immunomagnetic separation. Multiple markers are used in CTC identification, as epithelial markers and cytokeratines. CTC identification in peripheral blood is associated with a worse prognostic and reduced free survival in CRC.

Material and methods: We performed a systematic search in PubMed database for articles that reports the circulating tumor cells in CRC until July 2019. We selected studies in English and French and the main words used for search were ‘circulating tumor cells’, ‘colorectal cancer’, ‘colon cancer’, ‘rectal cancer’, ‘flow cytometry’, ‘peripheral blood’. We included studies with more than 10 patients, where samples were collected from the blood in relation with surgery and flow cytometry was used as analyzing technique.

Results: We included 7 studies in final analysis, that showed in flow cytometry analysis a cut-off value of CTC that can vary from 2-4 CTC/ 7.5 ml peripheral blood with a sensitivity of 50.8% and specificity of 95%. Patients with positive CTC were associated with higher T stage and positive lymph nodes, with a worse overall survival (OS) and disease free survival (DFS) comparing with negative patients.

Conclusion: CTC are considered to be a prognostic factor who needs more validation studies in order to be included in the clinical practice.

Prognostic factors differ according to KRAS mutational status: A classification and regression tree model to define prognostic groups after hepatectomy for colorectal liver metastasis

BACKGROUND

Although KRAS mutation status is known to affect the prognosis of patients with colorectal liver metastasis, the hierarchical association between other prognostic factors and KRAS status is not fully understood.

METHODS

Patients who underwent a hepatectomy for colorectal liver metastasis were identified in a multi-institutional international database. A classification and regression tree model was constructed to investigate the hierarchical association between prognostic factors and overall survival relative to KRAS status.

RESULTS

Among 1,123 patients, 29.9% (n = 336) had a KRAS mutation. Among wtKRAS patients, the classification and regression tree model identified presence of metastatic lymph nodes as the most important prognostic factor, whereas among mtKRAS patients, carcinoembryonic antigen level was identified as the most important prognostic factor. Among patients with wtKRAS, the highest 5-year overall survival (68.5%) was noted among patients with node negative primary colorectal cancer, solitary colorectal liver metastases, size <4.3 cm. In contrast, among patients with mtKRAS colorectal liver metastases, the highest 5-year overall survival (57.5%) was observed among patients with carcinoembryonic antigen <6 mg/mL. The classification and regression tree model had higher prognostic accuracy than the Fong score (wtKRAS [Akaike's Information Criterion]: classification and regression tree model 3334 vs Fong score 3341; mtKRAS [Akaike's Information Criterion]: classification and regression tree model 1356 vs Fong score 1396).

CONCLUSION

Machine learning methodology outperformed the traditional Fong clinical risk score and identified different factors, based on KRAS mutational status, as predictors of long-term prognosis.

Photoconversion and chromatographic microfluidic system reveals differential cellular phenotypes of adhesion velocity versus persistence in shear flow

An integrated photoconversion and cell sorting parallel-plate chromatography channel enabling the measurement of instantaneous and average velocities of cells mediating adhesion in flow fields was engineered to study the mechanisms underlying adhesion to selectins by metastatic cancer cells. Through the facile enrichment of cells into subfractions of differing adhesive behaviors and a fluorescent velocity probe amenable to off-chip analysis, underlying, causal molecular profiles implicated in differing adhesive phenotypes of metastatic cancer cells could be interrogated. This analytical method revealed selectin-mediated rolling adhesion to be strongly associated with expression of selectin ligands, correlations that vary with ligand type and rolling velocity magnitude. Discrete selectin ligand expression profiles were also found to underlie persistent versus non-persistent adhesion on selectins, suggestive of divergent regulatory mechanisms. This integrated cell sorting and photoconversion microfluidic platform thus enables in vitro analysis and comparisons of adhesive phenotypes as they relate to mechanisms of cancer cell metastasis in the context of selectin mediated adhesion, revealing new insights into potential cancer dissemination pathways.

The prognostic role of circulating tumor cells in colorectal cancer

Introduction: Metastasis is the main cause of cancer-associated death in colorectal cancer (CRC). The presence of circulating tumor cells (CTC) in the blood is associated with an increased risk of recurrence and poor prognosis. The clinical significance of CTCs as a novel biomarker has been extensively studied in the last decade. It has been shown that CTC detection applies to early cancer detection. The presence of CTCs is associated with metastatic spread and poor survival and is also useful as a marker for therapy response.Areas covered: We summarize the role of CTC in CRC, their clinical significance, current methods for CTC detection and challenges as well as future perspectives of CTC research.Expert commentary: The clinical significance of CTC in CRC patients is well established. Although insightful, the available marker-based approaches hampered our understanding of the CTCs and their biology, as such approaches do not take into account the heterogeneity of these cell populations. New technologies should expand the marker-based detection to multi biomarker-based approaches together with recent technological advances in microfluidics for single cell enrichment and analysis.

Chromosomal Aberrations Associated with Sequential Steps of the Metastatic Cascade in Colorectal Cancer Patients

BACKGROUND

Genomic information can help to identify colorectal tumors with high and low metastatic potential, thereby improving prediction of benefit of local and/or systemic treatment. Here we investigated chromosomal aberrations in relation to the different stages of the metastatic cascade: dissemination of tumor cells into the mesenteric vein, metastatic outgrowth in the liver, intravasation of the peripheral blood circulation, and development of further distant metastasis.

METHODS

Peripheral and mesenteric blood from colorectal cancer patients (n = 72) were investigated for circulating tumor cells, and DNA extracted from their primary tumors was subjected to array comparative genomic hybridization profiling. The results were validated with an independent set of primary colorectal tumors (n = 53) by quantitative reverse transcription PCR.

RESULTS

Mesenteric intravasation and liver metastasis were correlated with losses of chromosomes 16p (72%), 16q (27%), and 19 (54%), gain along 1q31 (45%) and 20q (60%), tumor cell infiltration into the peripheral blood circulation, and further distant metastasis with gain of chromosome 8q (59%) and 12 (47%, P < 0.01). Chromosome 12 gain was associated with poor overall survival in the initial (2.8 vs >7 years) and validation cohort (3.3 vs >6 years). The prospective study presented here is a hypothesis-generating study and confirmation with larger cohorts is required.

CONCLUSIONS

This is the first study that investigated colorectal cancer in its different stages of metastasis in correlation with copy number changes of the primary tumor. This information might be helpful to identify patients with limited metastatic spread who may profit from liver metastasis resection and may lead to the discovery of new therapeutic targets.Microarray data have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE82228.

D-dimer predicts postoperative recurrence and prognosis in patients with liver metastasis of colorectal cancer

BACKGROUND

Colorectal cancer is common, and its incidence is increasing throughout the world. The liver is a major metastatic site, and colorectal liver metastasis (CRLM) has a poor prognosis. Although liver resection is the most effective therapy for CRLM, postoperative recurrence is common. Thus, prognostic markers for CRLM are greatly needed. D-dimer, a fibrin cleavage product, has been shown to be related to colorectal tumor progression, and is also associated with malignant progression and recurrence in various cancers. Therefore, we evaluated the value of D-dimer in predicting the prognosis in CRLM.

METHODS

We retrospectively evaluated 90 cases of resected CRLM to determine the correlation between D-dimer and patient survival. The cut-off value for D-dimer levels was determined using receiver operating characteristic curve analysis.

RESULTS

Significant differences occurred in the recurrence group with higher D-dimer levels (P = 0.00736*), while the optimal cut-off value was 0.6 µg/mL. High D-dimer levels (≥ 0.6 µg/mL) were associated with poor recurrence-free survival (RFS; P = 0.0000841*) and cancer-specific survival (CSS; P = 0.00615*). In the multivariate analysis, D-dimer correlated with CRLM prognosis and independently predicted RFS (P = 0.0179*).

CONCLUSION

High D-dimer levels were associated with poor RFS and CSS. D-dimer was an independent prognostic factor of RFS. Therefore, D-dimer may help predict recurrence and prognosis in patients with CRLM.