Predicting lymph node metastasis in colorectal cancer patients: development and validation of a column chart model

Lymph node metastasis (LNM) is one of the crucial factors in determining the optimal treatment approach for colorectal cancer. The objective of this study was to establish and validate a column chart for predicting LNM in colon cancer patients. We extracted a total of 83,430 cases of colon cancer from the Surveillance, Epidemiology, and End Results (SEER) database, spanning the years 2010-2017. These cases were divided into a training group and a testing group in a 7:3 ratio. An additional 8545 patients from the years 2018-2019 were used for external validation. Univariate and multivariate logistic regression models were employed in the training set to identify predictive factors. Models were developed using logistic regression, LASSO regression, ridge regression, and elastic net regression algorithms. Model performance was quantified by calculating the area under the ROC curve (AUC) and its corresponding 95% confidence interval. The results demonstrated that tumor location, grade, age, tumor size, T stage, race, and CEA were independent predictors of LNM in CRC patients. The logistic regression model yielded an AUC of 0.708 (0.7038-0.7122), outperforming ridge regression and achieving similar AUC values as LASSO regression and elastic net regression. Based on the logistic regression algorithm, we constructed a column chart for predicting LNM in CRC patients. Further subgroup analysis based on gender, age, and grade indicated that the logistic prediction model exhibited good adaptability across all subgroups. Our column chart displayed excellent predictive capability and serves as a useful tool for clinicians in predicting LNM in colorectal cancer patients.

Refining Risk Criteria May Substantially Reduce Unnecessary Additional Surgeries after Local Resection of T1 Colorectal Cancer

BACKGROUND

The low positive predictive value for lymph node metastases (LNM) of common practice risk criteria (CPRC) in T1 colorectal carcinoma (CRC) leads to manyunnecessary additional surgeries following local resection. This study aimed to identify criteria that may improve on the CPRC.

METHODS

Logistic regression analysis was performed to determine the association of diverse variables with LNM or 'poor outcome' (LNM and/or distant metastases and/or recurrence) in a single center T1 CRC cohort. The diagnostic capacity of the set of variables obtained was compared with that of the CPRC.

RESULTS

The study comprised 161 cases. Poorly differentiated clusters (PDC) and tumor budding grade > 1 (TB > 1) were the only independent variables associated with LNM. The area under the curve (AUC) for these criteria was 0.808 (CI 95% 0.717-0.880) compared to 0.582 (CI 95% 0.479-0.680) for CPRC. TB > 1 and lymphovascular invasion (LVI) were independently associated with 'poor outcome', with an AUC of 0.801 (CI 95% 0.731-0.859), while the AUC for CPRC was 0.691 (CI 95% 0.603-0.752). TB > 1, combined either with PDC or LVI, would reduce false positives between 41.5% and 45% without significantly increasing false negatives.

CONCLUSIONS

Indicating additional surgery in T1 CRC only when either TB > 1, PDC, or LVI are present could reduce unnecessary surgeries significantly.

Preoperative prediction of lymph node metastasis in colorectal cancer using 18F-FDG PET/CT peritumoral radiomics analysis

BACKGROUND

Radiomics has been used in the diagnosis of tumor lymph node metastasis (LNM). However, to date, most studies have been based on intratumoral radiomics. Few studies have focused on the use of 18F-fluorodeoxyglucose positron emission computed tomography (18F-FDG PET/CT) peritumoral radiomics for the diagnosis of LNM in colorectal cancer (CRC).

PURPOSE

Determining the value of radiomics features extracted from 18F-FDG PET/CT images of the peritumoral region in predicting LNM in patients with CRC.

METHODS

The clinical data and preoperative 18F-FDG PET/CT images of 244 CRC patients were retrospectively analyzed. Intratumoral and peritumoral radiomics features were screened using the mutual information method, and least absolute shrinkage and selection operator regression. Based on the selected radiomics features, a radiomics score (Rad-score) was calculated, and independent risk factors obtained from univariate and multivariate logistic regression analyses were used to construct clinical and combined (Radiomics + Clinical) models. The performance of these models was evaluated using the DeLong test, while their clinical utility was assessed by decision curve analysis. Finally, a nomogram was constructed to visualize the predictive model.

RESULTS

The most optimal set of features retained by the feature filtering process were all peritumoral radiomic features. Carcinoembryonic antigen levels, PET/CT-reported lymph node status and Rad-score were found to be independent risk factors for LNM. All three LNM risk assessment models exhibited good predictive performance, with the combined model showing the best classification results, with areas under the curve of 0.85 and 0.76 in the training and validation groups, respectively. The DeLong test revealed that the performance of the combined model was superior to that of the clinical and radiomics models in both the training and validation groups, although this difference was only statistically significant in the training group. DCA indicated that the combined model displayed better clinical utility.

CONCLUSIONS

18F-FDG PET/CT peritumoral radiomics is uniquely suited to predict the presence of LNM in patients with CRC. In particular, the predictive efficacy of LNM for precision therapy and individualized patient management can be improved by using a combination of clinical risk factors.

Additional staining for lymphovascular invasion is associated with increased estimation of lymph node metastasis in patients with T1 colorectal cancer: Systematic review and meta-analysis

OBJECTIVES

Lymphovascular invasion (LVI) is a critical risk factor for lymph node metastasis (LNM), which requires additional surgery after endoscopic resection of T1 colorectal cancer (CRC). However, the impact of additional staining on estimating LNM is unclear. This systematic review aimed to evaluate the impact of additional staining on determining LNM in T1 CRC.

METHODS

We searched five electronic databases. Outcomes were diagnostic odds ratio (DOR), assessed using hierarchical summary receiver operating characteristic curves, and interobserver agreement among pathologists for positive LVI, assessed using Kappa coefficients (κ). We performed a subgroup analysis of studies that simultaneously included a multivariable analysis for other risk factors (deep submucosal invasion, poor differentiation, and tumor budding).

RESULTS

Among the 64 studies (18,097 patients) identified, hematoxylin-eosin (HE) and additional staining for LVI had pooled sensitivities of 0.45 (95% confidence interval [CI] 0.32-0.58) and 0.68 (95% CI 0.44-0.86), specificities of 0.88 (95% CI 0.78-0.94) and 0.76 (95% CI 0.62-0.86), and DORs of 6.26 (95% CI 3.73-10.53) and 6.47 (95% CI 3.40-12.32) for determining LNM, respectively. In multivariable analysis, the DOR of additional staining for LNM (DOR 5.95; 95% CI 2.87-12.33) was higher than that of HE staining (DOR 1.89; 95% CI 1.13-3.16) (P = 0.01). Pooled κ values were 0.37 (95% CI 0.22-0.52) and 0.62 (95% CI 0.04-0.99) for HE and additional staining for LVI, respectively.

CONCLUSION

Additional staining for LVI may increase the DOR for LNM and interobserver agreement for positive LVI among pathologists.

Differentiation grade as a risk factor for lymph node metastasis in T1 colorectal cancer

Objectives

Japanese guidelines include high-grade (poorly differentiated) tumors as a risk factor for lymph node metastasis (LNM) in T1 colorectal cancer (CRC). However, whether the grading is based on the least or most predominant component when the lesion consists of two or more levels of differentiation varies among institutions. This study aimed to investigate which method is optimal for assessing the risk of LNM in T1 CRC.

Methods

We retrospectively evaluated 971 consecutive patients with T1 CRC who underwent initial or additional surgical resection from 2001 to 2021 at our institution. Tumor grading was divided into low-grade (well- to moderately differentiated) and high-grade based on the least or predominant differentiation analyses. We investigated the correlations between LNM and these two grading analyses.

Results

LNM was present in 9.8% of patients. High-grade tumors, as determined by least differentiation analysis, accounted for 17.0%, compared to 0.8% identified by predominant differentiation analysis. A significant association with LNM was noted for the least differentiation method (p < 0.05), while no such association was found for predominant differentiation (p = 0.18). In multivariate logistic regression, grading based on least differentiation was an independent predictor of LNM (p = 0.04, odds ratio 1.68, 95% confidence interval 1.00-2.83). Sensitivity and specificity for detecting LNM were 27.4% and 84.1% for least differentiation, and 2.1% and 99.3% for predominant differentiation, respectively.

Conclusions

Tumor grading via least differentiation analysis proved to be a more reliable measure for assessing LNM risk in T1 CRC compared to grading by predominant differentiation.

Diagnostic Accuracy of Highest-Grade or Predominant Histological Differentiation of T1 Colorectal Cancer in Predicting Lymph Node Metastasis: A Systematic Review and Meta-Analysis

INTRODUCTION

Treatment guidelines for colorectal cancer (CRC) suggest 2 classifications for histological differentiation-highest grade and predominant. However, the optimal predictor of lymph node metastasis (LNM) in T1 CRC remains unknown. This systematic review aimed to evaluate the impact of the use of highest-grade or predominant differentiation on LNM determination in T1 CRC.

METHODS

The study protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO, registration number: CRD42023416971) and was published in OSF ( https://osf.io/TMAUN/ ) on April 13, 2023. We searched 5 electronic databases for studies assessing the diagnostic accuracy of highest-grade or predominant differentiation to determine LNM in T1 CRC. The outcomes were sensitivity and specificity. We simulated 100 cases with T1 CRC, with an LNM incidence of 11.2%, to calculate the differences in false positives and negatives between the highest-grade and predominant differentiations using a bootstrap method.

RESULTS

In 42 studies involving 41,290 patients, the differentiation classification had a pooled sensitivity of 0.18 (95% confidence interval [CI] 0.13-0.24) and 0.06 (95% CI 0.04-0.09) ( P < 0.0001) and specificity of 0.95 (95% CI 0.93-0.96) and 0.98 (95% CI 0.97-0.99) ( P < 0.0001) for the highest-grade and predominant differentiations, respectively. In the simulation, the differences in false positives and negatives between the highest-grade and predominant differentiations were 3.0% (range 1.6-4.4) and -1.3% (range -2.0 to -0.7), respectively.

DISCUSSION

Highest-grade differentiation may reduce the risk of misclassifying cases with LNM as negative, whereas predominant differentiation may prevent unnecessary surgeries. Further studies should examine differentiation classification using other predictive factors.

Long-term outcomes of endoscopic or surgical resection in T1 colorectal cancer patients: a retrospective cohort study

BACKGROUND

The personalized treatments of T1 colorectal cancer (CRC) remains controversial. We compared the long-term outcomes of T1 CRC patients after endoscopic resection (ER) and surgery, and evaluated the risk factors for the long-term prognosis.

METHODS

T1 CRCs after resection at the Cancer Hospital, Chines Academy of Medical Sciences from June 2011 to November 2021 were reviewed. High-risk factors included positive resection margin, poor differentiation, deep submucosal invasion (DSI ≥ 1000 μm), lymphovascular invasion and intermediate/high tumor budding. Comparative analyses were conducted based on three treatment methods: follow-up after ER (Group A), additional surgery after ER (Group B) and initial surgery (Group C). The primary endpoints included recurrence-free survival (RFS) and overall survival (OS). Cox proportional hazard regression models were constructed to identify risk factors for RFS and OS.

RESULTS

A total of 528 patients were enrolled (173 patients in Group A, 102 patients in Group B, 253 patients in Group C). The 3-year RFS, 5-year RFS, 3-year OS, and 5-year OS rates were 96.7%, 94.7%, 99.1%, and 97.8%, respectively. In the absence of other high-risk factors, RFS (P = 0.321) and OS (P = 0.155) of patients with DSI after ER were not inferior to those after surgery. Multivariate analyses identified sex (HR 0.379; 95% CI 0.160-0.894), Charlson comorbidities index (CCI) (HR 3.330; 95% CI 1.571-7.062), margin (HR 8.212; 95% CI 2.325-29.006), and budding (HR 3.794; 95% CI 1.686-8.541) as independent predictive factors of RFS, and identified CCI (HR 10.266; 95% CI 2.856-36.899) as an independent predictive factor of OS.

CONCLUSION

The long-term outcomes of ER are comparable to those of surgery in T1 CRC patients with DSI when other high-risk factors are negative. Resection margin, tumor budding, sex, and CCI may be the most important long-term prognostic factors for T1 CRC patients.

The absolute number of small and diminutive adenomas with high-grade dysplasia is substantially higher compared with large adenomas: a retrospective pooled study

Introduction

The risk that a large polyp (≥10 mm) evolves into high-grade dysplasia (HGD) is relatively high compared with that of a small/diminutive polyp (<10 mm). Recently, the detection of small and diminutive polyps has been substantially improved with the advancement of endoscopy. However, further research is needed on the role of the incidence of HGD caused by the co-occurrence of small and diminutive polyps in the progression of HGD. In this study, we aim to investigate whether and how the small and diminutive polyps correlate with the incidence of HGD in the population.

Methods

The pooled data were deeply analyzed from four published randomized controlled trials (RCTs) regarding colon polyp detection. All polyps detected were examined and confirmed by pathologists. The primary outcome was the composition ratio of the HGD polyps in each polyp size category.

Results

Among a total of 3,179 patients with 2,730 polyps identified, there were 83 HGD polyps confirmed, and 68 patients had at least one polyp with HGD. The risk of development of HGD was lower for a single small and diminutive polyp than for one large polyp (2.18% vs. 22.22%, P < 0.0001). On the contrary, the composition ratio for HGD from small and diminutive polyps was significantly higher than that from the large ones (68.67% vs. 31.33%, P < 0.0001). The combined number of HGD presented a trend negatively correlated to size.

Conclusions

Our data demonstrated that the absolute number of HGD significantly derives more from small and diminutive polyps than from the large ones, and the collective number of small and diminutive polyps per patient is indicative of his/her HGD exposure. These findings positively provide novel perspectives on the management of polyps and may further optimize the prevention of colorectal cancer.

Systematic Review Registration

http://www.chictr.org.cn, identifier ChiCTR1900025235, ChiCTR1800017675, ChiCTR1800018058, and ChiCTR1900023086.

Curative criteria for endoscopic treatment of colorectal cancer

As endoscopic treatment enables en bloc resection of T1 colorectal cancers, the risk of recurrence, often assimilated to the risk of lymph node metastases, must be assessed in order to offer patients an additional treatment if this risk is deemed significant. The curative criteria currently used by most guidelines are depth of invasion <1 mm, well or moderately differentiated tumour, absence of lympho-vascular invasion, absence of significant budding and tumour-free resection margins. However, these factors must be assessed by qualified pathologists, as they are difficult to evaluate. Moreover, the combination of these factors leads to unnecessary surgery in over 80 % of patients whose tumours are classified as high risk. Refinement of current criteria and research into new tumour and immunological markers are needed to better predict the actual risk of our patients.

Potential Molecular Markers Related to Lymph Node Metastasis and Stalk Resection Margins in Pedunculated T1 Colorectal Cancers Using Digital Spatial Profiling: A Pilot Study with a Small Case Series

There is a debate regarding the prediction of lymph node metastasis (LNM) in pedunculated T1 colorectal cancer (CRC). In this study with four cases of pedunculated T1 CRCs, we aimed to investigate gene expression variations based on the distance from the Haggitt line (HL) and identify potential molecular risk factors for LNM. By leveraging the Cancer Transcriptome Atlas and digital spatial profiling technology, we meticulously analyzed discrete regions, including the head, HL, proximal stalk region (300-1000 μm from HL), and distal stalk region (1500-2000 μm from HL) to identify spatially sequential molecular changes. Our findings showed significant overall gene expression variations among the head, proximal stalk, and distal stalk regions of pedunculated T1 CRCs compared to the control adenoma. Compared to LNM-negative T1 CRCs, LNM-positive T1 CRC showed that the expression of genes involved in immune-related pathways such as B2M, HLA-B, and HLA-E were significantly downregulated in the distal stalk region compared to the proximal stalk region. In summary, our results may tentatively suggest considering endoscopic resection of the stalk with a minimum 2000 μm margin from the HL, taking into account the gene expression alterations related to immune-related pathways. However, we acknowledge the limitations of this pilot study, notably the small case series, which may restrict the depth of interpretation. Further validation is imperative to substantiate these findings.

Are the width, length, depth, and area of submucosal invasion predictive of lymph node metastasis in pT1 colorectal cancer?

PURPOSE

Submucosa-limited (pathological T1, pT1) colorectal cancers (CRCs) pose a continuing challenge in the choice of treatment options, which range from local excision to radical surgery. The aim of this study was to evaluate the morphometric and morphologic risk factors associated with regional lymph node metastasis (LNM) in pT1 CRC.

METHODS

We performed a histological review of patients who underwent oncological resection between 2016 and 2022. Tumor grade, budding, poorly differentiated clusters (PDCs), cancer gland rupture, lymphovascular invasion (LVI), and presence of deep submucosal invasion (DSI), as well as width, length, total area, and area of DSI, were evaluated as potential risk factors for LNM.

RESULTS

A total of 264 cases of colon and rectal carcinomas with invasion into the submucosal layer (pT1) were identified. LNM was found in 46 of the 264 cases (17.4%). All morphometric parameters, as well as DSI (P=0.330), showed no significant association with LNM. High grade adenocarcinoma (P=0.050), budding (P=0.056), and PDCs (P<0.001) were associated with LNM. In the multivariate analysis, LVI presence remained the only significant independent risk factor (odds ratio, 15.7; 95% confidence interval, 8.5-94.9; P<0.001).

CONCLUSION

The DSI of T1 CRC, as well as other morphometric parameters of submucosal tumor spread, held no predictive value in terms of LNM. LVI was the only independent risk factor of LNM.

Differences in Factors Predicting Lymph Node Metastasis Between pT1 Rectal Cancer and pT1 Colon Cancer: A Retrospective Study

BACKGROUND

Studies have demonstrated conflicting results regarding factors that predict lymph node metastasis (LNM) in pT1 colorectal cancers. We hypothesized that these discrepancies could be related to different factors predicting LNM between rectal and colon cancer. This study aimed to compare predicting factors for LNM between pT1 rectal and colon cancer.

METHODS

This retrospective study evaluated a prospectively maintained database that included 380 patients with pT1 colorectal cancer from January 2010 to December 2020. Patients were grouped according to whether they had rectal or colon cancer, with or without LNM, and factors predicting LNM were analyzed.

RESULTS

In pT1 rectal cancer, LNM was associated with deeper submucosal (SM) invasion (P = .024) and a higher proportion of poorly differentiated tumors (P = .006). In pT1 colon cancer, LNM was associated with a higher proportion of moderately/poorly differentiated tumors (P = .002) and lymphatic invasion (P = .004). In the multivariate analysis for rectal cancer, depth of SM invasion (≥3000 μm) was an independent predictive factor for LNM (95% confidence interval [CI], 1.48-27.94; P = .013), whereas for colon cancer, moderately/poorly differentiated tumors (95% CI, 1.38-8.13; P = .008) and lymphatic invasion (95% CI, 1.44-11.78; P = .008) were independent predictive factors for LNM.

DISCUSSION

There were distinct differences in the factors predicting LNM between pT1 rectal cancer and colon cancer. These results suggest the necessity in differentiating between rectal and colon cancer when performing studies on LNM in pT1 colorectal cancer.

Risk Factors for Lymph Node Metastasis and Recurrence in T1 Colorectal Cancer: Analysis of 801 Patients in a Single Institute

OBJECTIVE

To identify risk factors for lymph node metastasis and postoperative recurrence of pT1 colorectal cancer by clinicopathological study of surgically resected cases.

METHODS

In 801 patients with pT1 colorectal cancer who underwent surgical resection with lymph node dissection between April 2007 and January 2021, we evaluated clinicopathological factors (age, gender, BMI, serum CEA level, tumor localization, additional resection after endoscopic treatment, operation time, blood loss, histological type, tumor size, vascular invasion, and central lymph node dissection). We performed univariate and multivariate analyses to examine risk factors for lymph node metastasis. We also examined risk factors for recurrence in 583 patients up to December 2017.

RESULTS

Lymph node metastasis was observed in 100/801 patients (12.5%). Multivariate analysis of lymph node metastasis showed that patients with positive lymphatic invasion (odds ratio 2.57, 95% CI 1.62-4.04, P < .0001), positive venous invasion (odds ratio 2.31, 95% CI 1.48-3.61, P = .0002), and histologically poorly differentiated type (odds ratio 4.54, 95% CI 1.35-15.2, P = .014) were identified as risk factors. Postoperative recurrence was observed in 18/580 patients (3.1%). Risk factors for postoperative recurrence were also examined, including preoperative endoscopic treatment (odds ratio 3.59, 95% CI 1.18-10.9, P = .024), positive venous invasion (odds ratio 3.63, 95% CI 1.22-10.8, P = .021), positive lymph node metastasis (odds ratio 4.91, 95% CI 1.10-21.8, P = .037) were extracted as risk factors.

DISCUSSION

In this study, venous invasion, lymphatic invasion, and histologically poorly differentiated type were identified as risk factors for lymph node metastasis in T1 colorectal cancer, and positive venous invasion, positive lymph node metastasis, and preoperative endoscopic treatment were identified as risk factors for recurrence. We hope that large prospective study will lead to the development of a more specific treatment strategy, including endoscopic treatment and additional surgical resection.

Circulating Tumor DNA: Towards More Individualized Treatment for Patients with Resectable Colorectal Cancer

PURPOSE

Despite curative-intent treatment, recurrence is common for patients with colorectal cancer (CRC).  Currently, prediction of disease recurrence and prognostication following surgery is based upon vague clinical factors and more precise and dynamic biomarkers for risk stratification and treatment decisions are urgently needed.  Circulating tumor DNA (ctDNA) is a promising biomarker for patients undergoing treatment for resectable CRC.

METHODS

In this review, we provide an overview of the data supporting current uses of ctDNA for CRC, including localized CRC and resectable colorectal liver metastases (CLM), as well as descriptions of important ongoing clinical trials using ctDNA in the care of patients with CRC.

RESULTS

The detection of ctDNA following curative-intent therapy is associated with disease recurrence, and multiple trials are investigating its role in determining need and duration for adjuvant therapy for localized CRC. In addition, ctDNA reliably predicts prognosis for patients with CLM, with trials underway studying ctDNA-guided treatment sequencing and intensity.

CONCLUSION

The detection of ctDNA is a sensitive and dynamic biomarker for disease recurrence in CRC. Many investigations are underway into ctDNA's potential role in surveillance and treatment algorithms, and it has the potential to become a critical biomarker to determine individualized strategies for treatment sequencing, choice, and duration of therapies.

Prediction of disease recurrence or residual disease after primary endoscopic resection of pT1 colorectal cancer-results from a large nationwide Danish study

PURPOSE

Risk assessment of disease recurrence in pT1 colorectal cancer is crucial in order to select the appropriate treatment strategy. The study aimed to develop a prediction model, based on histopathological data, for the probability of disease recurrence and residual disease in patients with pT1 colorectal cancer.

METHODS

The model dataset consisted of 558 patients with pT1 CRC who had undergone endoscopic resection only (n = 339) or endoscopic resection followed by subsequent bowel resection (n = 219). Tissue blocks and slides were retrieved from Pathology Departments from all regions in Denmark. All original slides were evaluated by one experienced gastrointestinal pathologist (TPK). New sections were cut and stained for haematoxylin and eosin (HE) and immunohistochemical markers. Missing values were multiple imputed. A logistic regression model with backward elimination was used to construct the prediction model.

RESULTS

The final prediction model for disease recurrence demonstrated good performance with AUC of 0.75 [95% CI 0.72-0.78], HL chi-squared test of 0.59 and scaled Brier score of 10%. The final prediction model for residual disease demonstrated medium performance with an AUC of 0.68 [0.63-0.72].

CONCLUSION

We developed a prediction model for the probability of disease recurrence in pT1 CRC with good performance and calibration based on histopathological data. Together with lymphatic and venous invasion, an involved resection margin (0 mm) as opposed to a margin of ≤ 1 mm was an independent risk factor for both disease recurrence and residual disease.

Lymph Node Molecular Analysis with OSNA Enables the Identification of pT1 CRC Patients at Risk of Recurrence: A Multicentre Study

Early-stage colorectal carcinoma (CRC)-pT1-is a therapeutic challenge and presents some histological features related to lymph node metastasis (LNM). A significant proportion of pT1 CRCs are treated surgically, resulting in a non-negligible surgical-associated mortality rate of 1.5-2%. Among these cases, approximately 6-16% exhibit LNM, but the impact on survival is unclear. Therefore, there is an unmet need to establish an objective and reliable lymph node (LN) staging method to optimise the therapeutic management of pT1 CRC patients and to avoid overtreating or undertreating them. In this multicentre study, 89 patients with pT1 CRC were included. All histological features associated with LNM were evaluated. LNs were assessed using two methods, One-Step Nucleic Acid Amplification (OSNA) and the conventional FFPE plus haematoxylin and eosin (H&E) staining. OSNA is an RT-PCR-based method for amplifying CK19 mRNA. Our aim was to assess the performance of OSNA and H&E in evaluating LNs to identify patients at risk of recurrence and to optimise their clinical management. We observed an 80.9% concordance in LN assessment using the two methods. In 9% of cases, LNs were found to be positive using H&E, and in 24.7% of cases, LNs were found to be positive using OSNA. The OSNA results are provided as the total tumour load (TTL), defined as the total tumour burden present in all the LNs of a surgical specimen. In CRC, a TTL ≥ 6000 CK19 m-RNA copies/µL is associated with poor prognosis. Three patients had TTL > 6000 copies/μL, which was associated with higher tumour budding. The discrepancies observed between the OSNA and H&E results were mostly attributed to tumour allocation bias. We concluded that LN assessment with OSNA enables the identification of pT1 CRC patients at some risk of recurrence and helps to optimise their clinical management.

Whole slide image-based prediction of lymph node metastasis in T1 colorectal cancer using unsupervised artificial intelligence

OBJECTIVES

Lymph node metastasis (LNM) prediction for T1 colorectal cancer (CRC) is critical for determining the need for surgery after endoscopic resection because LNM occurs in 10%. We aimed to develop a novel artificial intelligence (AI) system using whole slide images (WSIs) to predict LNM.

METHODS

We conducted a retrospective single center study. To train and test the AI model, we included LNM status-confirmed T1 and T2 CRC between April 2001 and October 2021. These lesions were divided into two cohorts: training (T1 and T2) and testing (T1). WSIs were cropped into small patches and clustered by unsupervised K-means. The percentage of patches belonging to each cluster was calculated from each WSI. Each cluster's percentage, sex, and tumor location were extracted and learned using the random forest algorithm. We calculated the areas under the receiver operating characteristic curves (AUCs) to identify the LNM and the rate of over-surgery of the AI model and the guidelines.

RESULTS

The training cohort contained 217 T1 and 268 T2 CRCs, while 100 T1 cases (LNM-positivity 15%) were the test cohort. The AUC of the AI system for the test cohort was 0.74 (95% confidence interval [CI] 0.58-0.86), and 0.52 (95% CI 0.50-0.55) using the guidelines criteria (P = 0.0028). This AI model could reduce the 21% of over-surgery compared to the guidelines.

CONCLUSION

We developed a pathologist-independent predictive model for LNM in T1 CRC using WSI for determination of the need for surgery after endoscopic resection.

TRIAL REGISTRATION

UMIN Clinical Trials Registry (UMIN000046992, https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000053590).

Prediction model for lymph node metastasis in superficial colorectal cancer: a better choice than computed tomography

BACKGROUND

Risk evaluation of lymph node metastasis (LNM) in superficial colorectal cancer resected by endoscopic surgery is critical for determining subsequent therapeutic strategies, but the role of existing clinical methods, including computed tomography, remains limited.

METHODS

Features of the nomogram were determined by logistic regression analysis, and the performance was validated by calibration plots, ROC curves and DCA curves in both the training set and the validation set.

RESULTS

A total of 608 consecutive superficial CRC cases were randomly divided into 426 training and 182 validation cases. Univariate and multivariate logistic regression analyses revealed that age < 50, tumour budding, lymphatic invasion and lower HDL levels were risk factors for LNM. Stepwise regression and the Hosmer‒Lemeshow goodness of fit test showed that the nomogram had good performance and discrimination, which was validated by ROC curves and calibration plots. Internal and external validation demonstrated that the nomogram had a higher C-index (training group, 0.749, validation group, 0.693). DCA and clinical impact curves graphically show that the use of the nomogram to predict LNM had remarkable predictive power. Finally, in comparison with CT diagnosis, the nomogram also visually showed higher superiority, as demonstrated by ROC, DCA and clinical impact curves.

CONCLUSION

Using common clinicopathologic factors, a noninvasive nomogram for individualized prediction of LNM after endoscopic surgery was conveniently established. Nomograms have great superiority in the risk stratification of LNM compared with traditional CT imaging.

CT morphological features for predicting the risk of lymph node metastasis in T1 colorectal cancer

OBJECTIVES

The aim of this study is to evaluate the feasibility of clinicopathological characteristics and computed tomography (CT) morphological features in predicting lymph node metastasis (LNM) for patients with T1 colorectal cancer (CRC).

METHODS

A total of 144 patients with T1 CRC who underwent CT scans and surgical resection were retrospectively included in our study. The clinicopathological characteristics and CT morphological features were assessed by two observers. Univariate and multiple logistic regression analyses were used to identify significant LNM predictive variables. Then a model was developed using the independent predictive factors. The predictive model was subjected to bootstrapping validation (1000 bootstrap resamples) to calculate the calibration curve and relative C-index.

RESULTS

LNM were found in 30/144 patients (20.83%). Four independent risk factors were determined in the multiple logistic regression analysis, including presence of necrosis (adjusted odds ratio [OR] = 10.32, 95% confidence interval [CI] 1.96-54.3, p = 0.004), irregular outer border (adjusted OR = 5.94, 95% CI 1.39-25.45, p = 0.035), and heterogeneity enhancement (adjusted OR = 7.35, 95% CI 3.11-17.38, p = 0.007), as well as tumor location (adjusted ORright-sided colon = 0.05 [0.01-0.60], p = 0.018; adjusted ORrectum = 0.22 [0.06-0.83], p = 0.026). In the internal validation cohort, the model showed good calibration and good discrimination with a C-index of 0.89.

CONCLUSIONS

There are significant associations between lymphatic metastasis status and tumor location as well as CT morphologic features in T1 CRC, which could help the doctor make decisions for additional surgery after endoscopic resection.

KEY POINTS

• LNM more frequently occurs in left-sided T1 colon cancer than in right-sided T1 colon and rectal cancer. • CT morphologic features are risk factors for LNM of T1 CRC, which may be related to fundamental biological behaviors. • The combination of tumor location and CT morphologic features can more effectively assist in predicting LNM in patients with T1 CRC, and decrease the rate of unnecessary extra surgeries after endoscopic resection.

Endoscopic Treatment of T1 Colorectal Cancer

Commonly accepted criteria for curative resection of T1 colorectal cancer include R0 resection with horizontal and vertical clear margins (R0), absence of lympho-vascular or vessel infiltration (L0, V0), a low to moderate histological grading (G1/2), low tumor cell budding, and limited (<1000 µm) infiltration into the submucosa. However, submucosal infiltration depth in the absence of other high-risk features has recently been questioned as a high-risk situation for lymph-node metastasis. Consequently, endoscopic resection techniques should focus on the acquisition of qualitatively and quantitively sufficient submucosal tissue. Here, we summarize the current literature on lymph-node metastasis risk after endoscopic resection of T1 colorectal cancer. Moreover, we discuss different endoscopic resection techniques with respect to the quality of the resected specimen.

Diverse Sphingolipid Profiles in Rectal and Colon Cancer

Colorectal cancer is a heterogenous group of neoplasms showing a variety of clinical and pathological features depending on their anatomical location. Sphingolipids are involved in the formation and progression of cancers, and their changes are an important part of the abnormalities observed during carcinogenesis. Because the course of rectal and colonic cancer differs, the aim of the study was to assess whether the sphingolipid profile is also different in tumors of these two regions. Using a combination of ultra-high-performance liquid chromatography combined with triple quadrupole mass spectrometry, differences in the amounts of cellular sphingolipids were found in colorectal cancer. Sphingosine content was higher in rectal cancer than in adjacent healthy tissue, while the content of two ceramides (C18:0-Cer and C20:0-Cer) was lower. In colon cancer, a higher content of sphingosine, sphinganine, sphingosine-1-phosphate, and two ceramides (C14:0-Cer and C24:0-Cer) was found compared to healthy tissue, but there was no decrease in the amount of any of the assessed sphingolipids. In rectal cancer, the content of sphinganine and three ceramides (C16:0-Cer, C22:0-Cer, C24:0-Cer), as well as the entire pool of ceramides, was significantly lower compared to colon cancer. The S1P/Cer ratio in rectal cancer (S1P/C18:1-Cer, S1P/C20:0-Cer, S1P/C22:0-Cer, S1P/C24:1-Cer) and in colon cancer (S1P/C18:0-Cer, S1P/C18:1-Cer, S1P/C20:0-Cer) was higher than in adjacent healthy tissue and did not differ between the two sites (rectal cancer vs. colonic cancer). It seems that the development of colorectal cancer is accompanied by complex changes in the metabolism of sphingolipids, causing not only qualitative shifts in the ceramide pool of cancer tissue but also quantitative disturbances, depending on the location of the primary tumor.

"Transanal endoscopic microsurgery" with a flexible colonoscope (F-TEM): a new endoscopic treatment for suspicious deep submucosal invasion T1 rectal carcinoma

BACKGROUND

Endoscopic techniques allow resections of deep submucosal invasion rectal carcinoma, but mostly are facing issues such as costs, follow-up care or size limit. Our aim was to design a new endoscopic technique, which retains the advantages over surgical resections while eliminating the disadvantages mentioned above.

PATIENTS AND METHODS

We propose a technique for the resection of the superficial rectal tumours, with highly suspicious deep submucosal invasion. It combines steps of endoscopic submucosal dissection, muscular resection and edge-to-edge suture of the muscular layers, finally performing the equivalent of a "transanal endoscopic microsurgery" with a flexible colonoscope (F-TEM).

RESULTS

A 60-year-old patient was referred to our unit, following the discovery of a 15 mm distal rectum adenocarcinoma. The computed tomography and the endoscopic ultrasound examination revealed a T1 tumour, without secondary lesions. Considering that the initial endoscopic evaluation highlighted a depressed central part of the lesion, with several avascular zones, an F-TEM was performed, without severe complication. The histopathological examination revealed negative resection margins, without risk factors for lymph node metastasis, no adjuvant therapy being proposed.

CONCLUSION

F-TEM allows endoscopic resection of highly suspicious deep submucosal invasion T1 rectal carcinoma and it proves to be a feasible alternative to surgical resection or other endoscopic treatments as endoscopic submucosal dissection or intermuscular dissection.

Lymph node metastasis in T1-2 colorectal cancer: a population-based study

BACKGROUND

We performed this study to identify predictive factors for lymph node metastasis (LNM) and analyze the impact of LNM on the prognosis of patients with T1-2 colorectal cancer (CRC), with the intention of providing guidance for the treatment.

METHODS

The Surveillance Epidemiology and End Result database was used to identify 20,492 patients diagnosed with T1-2 stage CRC between 2010 and 2019, who underwent surgery and lymph node evaluation and had complete prognostic information. Clinicopathological data of patients with T1-2 stage colorectal cancer treated with surgery at Peking University People's Hospital from 2017 to 2021 with complete clinical information were retrieved. We identify and confirm the risk factors for positive lymph node involvement, and the results of follow-up were analyzed.

RESULTS

Age, preoperative carcinoembryonic antigen (CEA) level, perineural invasion, and primary tumor site were independent risk factors for LNM in T1-2 CRC based on the analysis of the SEER database, while tumor size and histology of mucinous carcinoma were also independent risk factors in T1 CRC. We then make the nomogram model for predicting LNM risk and showed an acceptable consistency and calibration capability. Survival analysis showed that LNM was an independent prognostic indicator of 5-year disease-specific survival (P = 0.013) and disease-free survival (P < 0.001) in patients with T1 and T2 CRC.

CONCLUSION

Age, CEA level and primary tumor site should be taken into consideration before making the surgical decision in T1-2 CRC patients. The tumor size and histology of mucinous carcinoma also need to be thought about in T1 CRC. Conventional imaging tests do not appear to provide a precise assessment for this issue.

Fibroblast Activation Protein Inhibitor-PET Imaging in Colorectal Cancer

Fibroblast activation protein inhibitor (FAPI)-PET imaging holds great promise for improving the clinical management of colorectal cancer. High fibroblast activation protein expression is particularly observed in lymph node metastases, in the aggressive Consensus Molecular Subtype 4, in peritoneal metastases, and in tumors that respond poorly to immunotherapy. We have defined six clinical dilemmas in the diagnosis and treatment of colorectal cancer, which FAPI-PET may help solve. Future clinical trials should include patients undergoing tumor resection, allowing correlation of FAPI-PET signals with in-depth histopathological, cellular, and molecular tissue analyses.

New Personal Model for Forecasting the Outcome of Patients with Histological Grade III-IV Colorectal Cancer Based on Regional Lymph Nodes

Background

Metastases at regional lymph nodes could easily occur in patients with high-histological-grade colorectal cancer (CRC). However, few models were built on the basis of lymph nodes to predict the outcome of patients with histological grades III-IV CRC.

Methods

Data in the Surveillance, Epidemiology, and End Results databases were used. Univariate and multivariate analyses were performed. A personalized prediction model was built in accordance with the results of the analyses. A nomogram was tested in two datasets and assessed using a calibration curve, a consistency index (C-index), and an area under the curve (AUC).

Results

A total of 14,039 cases were obtained from the database. They were separated into two groups (9828 cases for constructing the model and 4211 cases for validation). Logistic and Cox regression analyses were then conducted. Factors such as log odds of positive lymph nodes (LODDS) were utilized. Then, a personalized prediction model was established. The C-index in the construction and validation groups was 0.770. The 1-, 3-, and 5-year AUCs were 0793, 0.828, and 0.830 in the construction group, respectively, and 0.796, 0.833, and 0.832 in the validation group, respectively. The calibration curves showed well consistency in the 1-, 3- and 5-year OS between prediction and reality in both groups.

Conclusion

The nomogram built based on LODDS exhibited considerable reliability and accuracy.

Development and validation of an artificial intelligence-based system for predicting colorectal cancer invasion depth using multi-modal data

OBJECTIVES

Accurate endoscopic optical prediction of the depth of cancer invasion is critical for guiding an optimal treatment approach of large sessile colorectal polyps but was hindered by insufficient endoscopists expertise and inter-observer variability. We aimed to construct a clinically applicable artificial intelligence (AI) system for the identification of presence of cancer invasion in large sessile colorectal polyps.

METHODS

A deep learning-based colorectal cancer invasion calculation (CCIC) system was constructed. Multi-modal data including clinical information, white light (WL) and image-enhanced endoscopy (IEE) were included for training. The system was trained using 339 lesions and tested on 198 lesions across three hospitals. Man-machine contest, reader study and video validation were further conducted to evaluate the performance of CCIC.

RESULTS

The overall accuracy of CCIC system using image and video validation was 90.4% and 89.7%, respectively. In comparison with 14 endoscopists, the accuracy of CCIC was comparable with expert endoscopists but superior to all the participating senior and junior endoscopists in both image and video validation set. With CCIC augmentation, the average accuracy of junior endoscopists improved significantly from 75.4% to 85.3% (P = 0.002).

CONCLUSIONS

This deep learning-based CCIC system may play an important role in predicting the depth of cancer invasion in colorectal polyps, thus determining treatment strategies for these large sessile colorectal polyps.

The CT-based intratumoral and peritumoral machine learning radiomics analysis in predicting lymph node metastasis in rectal carcinoma

Background

To construct clinical and machine learning nomogram for predicting the lymph node metastasis (LNM) status of rectal carcinoma (RC) based on radiomics and clinical characteristics.

Methods

788 RC patients were enrolled from January 2015 to January 2021, including 303 RCs with LNM and 485 RCs without LNM. The radiomics features were calculated and selected with the methods of variance, correlation analysis, and gradient boosting decision tree. After feature selection, the machine learning algorithms of Bayes, k-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and decision tree (DT) were used to construct prediction models. The clinical characteristics combined with intratumoral and peritumoral radiomics was taken to develop a radiomics and machine learning nomogram. The relative standard deviation (RSD) was used to predict the stability of machine learning algorithms. The area under curves (AUCs) with 95% confidence interval (CI) were calculated to evaluate the predictive efficacy of all models.

Results

To intratumoral radiomics analysis, the RSD of Bayes was minimal compared with other four machine learning algorithms. The AUCs of arterial-phase based intratumoral Bayes model (0.626 and 0.627) were higher than these of unenhanced-phase and venous-phase ones in both the training and validation group.The AUCs of intratumoral and peritumoral Bayes model were 0.656 in the training group and were 0.638 in the validation group, and the relevant Bayes-score was quantified. The clinical-Bayes nomogram containing significant clinical variables of diameter, PNI, EMVI, CEA, and CA19-9, and Bayes-score was constructed. The AUC (95%CI), specificity, and sensitivity of this nomogram was 0.828 (95%CI, 0.800-0.854), 74.85%, and 77.23%.

Conclusion

Intratumoral and peritumoral radiomics can help predict the LNM status of RCs. The machine learning algorithm of Bayes in arterial-phase conducted better in consideration of terms of RSD and AUC. The clinical-Bayes nomogram achieved a better performance in predicting the LNM status of RCs.

Current problems and perspectives of pathological risk factors for lymph node metastasis in T1 colorectal cancer: Systematic review

With the prevalence of endoscopic submucosal dissection and endoscopic full thickness resection, which enable complete resection of T1 colorectal cancer with a negative margin, the treatment strategy following endoscopic resection has become more important. The necessity of secondary surgical resection is determined on the basis of the risk of lymph node metastasis according to the histopathological findings of resected specimens because ~10% of T1 colorectal cancer cases have lymph node metastasis. The current Japanese treatment guidelines state four risk factors for lymph node metastasis: lymphovascular invasion, histological differentiation, depth of submucosal invasion, and tumor budding. These guidelines have succeeded in stratifying the low-risk group for lymph node metastasis, in which endoscopic resection alone is acceptable for cure. On the other hand, there are some problems: there is variation in diagnosis methods and low interobserver agreement for each pathological factor and 90% of surgical resections are unnecessary, with lymph node metastasis negativity. To ensure patients with T1 colorectal cancer receive more appropriate treatment, these problems should be addressed. In this systematic review, we gave some suggestions to these practical issues of four pathological factors as predictors.

Deep Submucosal Invasion Is Not an Independent Risk Factor for Lymph Node Metastasis in T1 Colorectal Cancer: A Meta-Analysis

BACKGROUND & AIMS

Deep submucosal invasion (DSI) is considered a key risk factor for lymph node metastasis (LNM) and important criterion to recommend surgery in T1 colorectal cancer. However, metastatic risk for DSI is shown to be low in the absence of other histologic risk factors. This meta-analysis determines the independent risk of DSI for LNM.

METHODS

Suitable studies were included to establish LNM risk for DSI in univariable analysis. To assess DSI as independent risk factor, studies were eligible if risk factors (eg, DSI, poor differentiation, lymphovascular invasion, and high-grade tumor budding) were simultaneously included in multivariable analysis or LNM rate of DSI was described in absence of poor differentiation, lymphovascular invasion, and high-grade tumor budding. Odds ratios (OR) and 95% CIs were calculated.

RESULTS

Sixty-seven studies (21,238 patients) were included. Overall LNM rate was 11.2% and significantly higher for DSI-positive cancers (OR, 2.58; 95% CI, 2.10-3.18). Eight studies (3621 patients) were included in multivariable meta-analysis and did not weigh DSI as a significant predictor for LNM (OR, 1.73; 95% CI, 0.96-3.12). As opposed to a significant association between LNM and poor differentiation (OR, 2.14; 95% CI, 1.39-3.28), high-grade tumor budding (OR, 2.83; 95% CI, 2.06-3.88), and lymphovascular invasion (OR, 3.16; 95% CI, 1.88-5.33). Eight studies (1146 patients) analyzed DSI as solitary risk factor; absolute risk of LNM was 2.6% and pooled incidence rate was 2.83 (95% CI, 1.66-4.78).

CONCLUSIONS

DSI is not a strong independent predictor for LNM and should be reconsidered as a sole indicator for oncologic surgery. The expanding armamentarium for local excision as first-line treatment prompts serious consideration in amenable cases to tailor T1 colorectal cancer management.

Colorectal submucosa thickness in specimens obtained by EMR versus ESD: a retrospective pilot study

Accurate histopathology is the mainstay for reliable classification of resected early colorectal cancer lesions in terms of potential risk of lymph node metastasis. In particular, thickness of resected submucosa is important in cases of submucosal invasive cancer. Nevertheless, little is known about the quality and thickness of submucosal tissue obtained using different endoscopic resection techniques. In this small pilot study, we performed morphometric analysis of submucosal thickness in specimens obtained from right-sided colorectal lesions using endoscopic mucosal resection (EMR) versus endoscopic submucosal resection (ESD). Comparative measurements showed significant differences in submucosal area ≥ 1000 μm and minimum submucosal thickness per tissue section analyzed (EMR vs. ESD: 91.2 % ± 6.6 vs. 47.1 % ± 10.6, P = 0.018; 933.7 µm ± 125.1 vs. 319.0 µm ± 123.6, P = 0.009). In contrast, no significant differences were observed in variation coefficient and mean maximum submucosal thickness. Thus, unexpectedly, in this small retrospective pilot study, specimens obtained using EMR had a better preserved submucosal layer than those obtained using ESD – possibly due to the different methods of specimen acquisition. The findings should be kept in mind when attempting to resect lesions suspicious for submucosal invasive cancer.

Comparison of Prognosis and Lymph Node Metastasis in T1-Stage Colonic and Rectal Carcinoma: A Retrospective Study

Background

Limited evidence and contradictory results have been reported regarding the impact of tumor site on lymph node metastasis (LNM) and prognosis in T1 stage adenocarcinoma (AC). We aimed to compare two anatomic locations in terms of LNM and prognosis using a comprehensive statistical analysis of a large population.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database and our center (First Affiliated Hospital of Nanchang University) were used to extract patient information. Univariate and multivariate logistic or Cox regression and propensity score matching were used to explore the association between LNM/survival and tumor site.

Results

Information for 12,404 patients, including 9655 colonic AC and 2749 rectal AC patients, was extracted from the SEER database. The 516 AC patients included 184 colonic and 332 rectal AC patients from our center. Multivariate logistic regression analysis revealed a correlation between LNM and tumor site (colon vs rectum, odds ratio [OR] =1.52, 95% CI, 1.349–1.714, P<0.001). Additionally, we found that younger age, T1b stage, poor differentiation, and lymphatic invasion were risk factors for LNM. After adjusting for confounding factors by PSM, we found that the location of the rectum remained a higher risk factor for LNM. However, we found that patients diagnosed with rectal AC had a prognosis similar to that of patients diagnosed with colonic AC, which was demonstrated by the analysis of SEER data and data from our center.

Conclusion

T1-stage rectal AC may have a higher risk of LNM than colonic AC, while rectal AC has a prognosis similar to that of colonic AC.

Predictive and Prognostic Assessment Models for Tumor Deposit in Colorectal Cancer Patients With No Distant Metastasis

Background

More and more evidence indicated that tumor deposit (TD) was significantly associated with local recurrence, distant metastasis (DM), and poor prognosis for patients with colorectal cancer (CRC). This study aims to explore the main clinical risk factors for the presence of TD in CRC patients with no DM (CRC-NDM) and the prognostic factors for TD-positive patients after surgery.

Methods

The data of patients with CRC-NDM between 2010 and 2017 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. A logistic regression model was used to identify risk factors for TD presence. Fine and Gray’s competing-risk model was performed to analyze prognostic factors for TD-positive CRC-NDM patients. A predictive nomogram was constructed using the multivariate logistic regression model. The concordance index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and the calibration were used to evaluate the predictive nomogram. Also, a prognostic nomogram was built based on multivariate competing-risk regression. C-index, the calibration, and decision-curve analysis (DCA) were performed to validate the prognostic model.

Results

The predictive nomogram to predict the presence of TD had a C-index of 0.785 and AUC of 0.787 and 0.782 in the training and validation sets, respectively. From the competing-risk analysis, chemotherapy (subdistribution hazard ratio (SHR) = 0.542, p < 0.001) can significantly reduce CRC-specific death (CCSD). The prognostic nomogram for the outcome prediction in postoperative CRC-NDM patients with TD had a C-index of 0.727. The 5-year survival of CCSD was 17.16%, 36.20%, and 63.19% in low-, medium-, and high-risk subgroups, respectively (Gray’s test, p < 0.001).

Conclusions

We constructed an easily predictive nomogram in identifying the high-risk TD-positive CRC-NDM patients. Besides, a prognostic nomogram was built to help clinicians identify poor-outcome individuals in postoperative CRC-NDM patients with TD. For the high-risk or medium-risk subgroup, additional chemotherapy may be more advantageous for the TD-positive patients rather than radiotherapy.

Tumor Location as a Prognostic Factor in T1 Colorectal Cancer

The incidence of T1 colorectal cancer is expected to increase because of the prevalence of colorectal cancer screening and the progress of endoscopic treatment such as endoscopic submucosal dissection or endoscopic full-thickness resection. Currently, the requirement for additional surgery after endoscopic resection of T1 colorectal cancer is determined according to several treatment guidelines (in USA, Europe, and Japan) referring to the following pathological findings: lymphovascular invasion, tumor differentiation, depth of invasion, and tumor budding, all of which are reported to be risk factors for lymph node metastasis. In addition to these factors, in this review, we investigate whether tumor location, which is an objective factor, has an impact on the presence of lymph node metastasis and recurrence. From recent studies, left-sided location, especially the sigmoid colon in addition to rectum, could be a risk factor for lymph node metastasis and cancer recurrence. The treatment of T1 colorectal cancer should be managed considering these findings.

Supervised Learning Based Systemic Inflammatory Markers Enable Accurate Additional Surgery for pT1NxM0 Colorectal Cancer: A Comparative Analysis of Two Practical Prediction Models for Lymph Node Metastasis

Purpose

Predicting lymph node metastasis (LNM) after endoscopic resection is crucial in determining whether patients with pT1NxM0 colorectal cancer (CRC) should undergo additional surgery. This study was aimed to develop a predictive model that can be used to reduce the current likelihood of overtreatment.

Patients and Methods

We recruited a total of 1194 consecutive CRC patients with pT1NxM0 who underwent endoscopic or surgical resection at the Gezhouba Central Hospital of Sinopharm between January 1, 2006, and August 31, 2021. The random forest classifier (RFC) and generalized linear algorithm (GLM) were used to screen out the variables that greatly affected the LNM prediction, respectively. The area under the curve (AUC) and decision curve analysis (DCA) were applied to assess the accuracy of predictive models.

Results

Analysis identified the top 10 candidate factors including depth of submucosal invasion, neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), platelet-to-neutrophil ratio(PNR), venous invasion, poorly differentiated clusters, tumor budding, grade, lymphatic vascular invasion, and background adenoma. The performance of the GLM achieved the highest AUC of 0.79 (95% confidence interval [CI]: 0.30 to 1.28) in the training cohort and robust AUC of 0.80 (95% confidence interval [CI]: 0.36 to 1.24) in the validation cohort. Meanwhile, the RFC exhibited a robust AUC of 0.84 (95% confidence interval [CI]: 0.40 to 1.28) in the training cohort and a high AUC of 0.85 (95% CI: 0.41 to 1.29) in the validation cohort. DCAs also showed that the RFC had superior predictive ability.

Conclusion

Our supervised learning-based model incorporating histopathologic parameters and inflammatory markers showed a more accurate predictive performance compared to the GLM. This newly supervised learning-based predictive model can be used to determine an individually tailored treatment strategy.

DENEB: Development of new criteria for curability after local excision of pathological T1 colorectal cancer using liquid biopsy

According to the current international guidelines, high‐risk patients diagnosed with pathological T1 (pT1) colorectal cancer (CRC) who underwent complete local resection but may have risk of developing lymph node metastasis (LNM) are recommended additional intestinal resection with lymph node dissection. However, around 90% of the patients without LNM are exposed to the risk of being overtreated due to the insufficient pathological criteria for risk stratification of LNM. Circulating tumor DNA (ctDNA) is a noninvasive biomarker for molecular residual disease and relapse detection after treatments including surgical and endoscopic resection of solid tumors. The CIRCULATE‐Japan project includes a large‐scale patient‐screening registry of the GALAXY study to track ctDNA status of patients with stage II to IV or recurrent CRC that can be completely resected. Based on the CIRCULATE‐Japan platform, we launched DENEB, a new prospective study, within the GALAXY study for patients with pT1 CRC who underwent complete local resection and were scheduled for additional intestinal resection with lymph node dissection based on the standard pathologic risk stratification criteria for LNM. The aim of this study is to explore the ability of predicting LNM using ctDNA analysis compared with the standard pathological criteria. The ctDNA assay will build new evidence to establish a noninvasive personalized diagnosis in patients, which will facilitate tailored/optimal treatment strategies for CRC patients.

Deep Learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer

The spread of early-stage (T1 and T2) adenocarcinomas to loco-regional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomarkers are imperfect. Here, we used an end-to-end Deep Learning algorithm to identify risk factors for lymph node metastasis (LNM) status in digitized histopathology slides of the primary CRC and its surrounding tissue. In two large population-based cohorts, we show that this system can predict the presence of more than one LNM in pT2 CRC patients with an area under the receiver operating curve (AUROC) of 0.733 (0.67-0.758) and patients with any LNM with an AUROC of 0.711 (0.597-0.797). Similarly, in pT1 CRC patients, the presence of more than one LNM or any LNM was predictable with an AUROC of 0.733 (0.644-0.778) and 0.567 (0.542-0.597), respectively. Based on these findings, we used the Deep Learning system to guide human pathology experts towards highly predictive regions for LNM in the whole slide images. This hybrid human observer and Deep Learning approach identified inflamed adipose tissue as the highest predictive feature for LNM presence. Our study is a first proof of concept that artificial intelligence (AI) systems may be able to discover potentially new biological mechanisms in cancer progression. Our Deep Learning algorithm is publicly available and can be used for biomarker discovery in any disease setting. This article is protected by copyright. All rights reserved.

Prognostic implications of ENE and LODDS in relation to lymph node-positive colorectal cancer location

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This is the first study on LODDS and ENE together. The current study showed that LODDS and ENE are liable prognostic parameters of CRC or CC.

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ENE is an independent influencing factor on the prognosis of both CRC and CC, and the prognostic impact of ENE was observed in both CRC and CC.

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The frequency of ENE increases from the proximal (right) to the distal (left) colon as well as the rectum.

Background

Extranodal extension (ENE) and log odds of positive lymph nodes (LODDS) are associated with the aggressiveness of both colon and rectal cancers. The current study evaluated the clinicopathological significance and the prognostic impact of ENE and LODDS in the colon and rectal patients independently.

Methods

The clinical and histological records of 389 colorectal cancer (CRC) patients who underwent curative surgery were reviewed.

Results

For the ENE system, 244 patients were in the ENE1 group and 145 in the ENE2 system. Compared with the ENE1 system, the patients included in the ENE2 system were prone to nerve invasion (P < 0.001) and vessel invasion (P < 0.001) with higher TNM (P = 0.009), higher T category (P = 0.003), higher N category (P < 0.001), advanced differentiation (P = 0.013), more number of positive lymph nodes (NPLN) (P < 0.001), more lymph node ratio (LNR) (P < 0.001), and a higher value of LODDS (P < 0.001). ENE was more frequent in patients with left and rectal than right cancer. For the LODDS system, 280 patients were in the LODDS1 group, and 109 in the LODDS2 group. Compared to the LODDS1 group, the patients included in the LODDS2 group were more prone to nerve invasion (P = 0.0351) and vessel invasion (P < 0.001) with a higher rate of N2 stage, less NDLN (P < 0.001), more NPLN (P < 0.001), more LNR (P < 0.001), and a higher value of ENE (P < 0.001). Based on the results in the univariable analysis, the N, NPLN, LNR, LODDS, and ENE were separately incorporated into five different Cox regression models combined with the same confounders. The multivariable Cox regression analysis demonstrated that all the five staging systems were independent prognostic factors for overall survival.

Conclusion

The current study confirmed that the LODDS stage is an independent influence on the prognosis of both CRC and CC patients. ENE is an independent influencing factor on the prognosis of both CRC and CC patients, and the prognostic impact of extracapsular lymph node was observed in both CRC and CC. The frequency of ENE increases from the proximal (right) to the distal (left) colon as well as the rectum. Therefore, combining ENE and LODDS into the current TNM system to compensate for the inadequacy of pN staging needs further investigation.

Association Between Chemotherapy and Survival in T1 Colon Cancer With Lymph Node Metastasis: A Propensity-Score Matched Analysis

This study aimed to comprehensively examine the efficacy of chemotherapy in T1 colon cancer patients with lymph node metastasis.

Higher LNM rate and poorer prognosis of early-onset compared to late-onset T1 stage colorectal cancer: a large-population based study

As for T1 stage CRC, there is little knowledge of differences in lymph node metastasis (LNM) and prognosis between early-onset and late-onset CRC. To know that, we included 13,084 patients from the SEER database and 476 patients in T1 stage from our hospital to analyze difference of LNM and prognosis. Univariate and multivariate logistic analyses revealed that early-onset CRC was more likely than late-onset CRC to be positive for LNM. In addition, we found that T1b stage, poor differentiation and lymphatic invasion were risk factors for LNM. Specifically, we found that black race was a risk factor. Before propensity-score matching (PSM), we also found that early-onset CRC patients had better survival, as demonstrated by SEER data. After adjusting for confounding factors by PSM, we found that early onset remained a risk factor for LNM. Moreover, we found that patients diagnosed with early-onset CRC had a poorer prognosis than those diagnosed with late-onset CRC, which was demonstrated by analysis of SEER data and our own data. In conclusion, our study was the first to find that early-onset T1 stage CRC more frequently developed LNM, suggesting that endoscopic submucosal resection should be performed more carefully in these patients. Moreover, early-onset patients in the T1 stage also had poorer survival, suggesting that clinical doctors should pay more attention to early-onset patients.