Meta-analysis of histopathological features of primary colorectal cancers that predict lymph node metastases

DNA methylation biomarkers for predicting lymph node metastasis in colorectal cancer

Colorectal cancer is one of the most common cancers worldwide. Lymph node metastasis is an important marker of colorectal cancer progression and plays a key role in the evaluation of patient prognosis. Accurate preoperative assessment of lymph node metastasis is crucial for devising appropriate treatment plans. However, current clinical imaging methods have limitations in many aspects. Therefore, the discovery of a method for accurately predicting lymph node metastasis is crucial clinical decision-making. DNA methylation is a common epigenetic modification that can regulate gene expression, which also has an important impact on the development of colorectal cancer. It is considered to be a promising biomarker with good specificity and stability and has promising application in predicting lymph node metastasis in patients with colorectal cancer. This article reviews the characteristics and limitations of currently available methods for predicting lymph node metastasis in patients with colorectal cancer and discusses the role of DNA methylation as a biomarker.

Diagnostic performance of Node Reporting and Data System (Node-RADS) for assessing mesorectal lymph node in rectal cancer by CT

BACKGROUND

To compare the diagnostic performance of the Node-RADS scoring system and lymph node (LN) size in preoperative LN assessment for rectal cancer (RC), and to investigate whether the selection of size as the primary criterion whereas morphology as the secondary criterion for LNs can be considered the preferred method for clinical assessment.

METHODS

Preoperative CT data of 146 RC patients treated with radical resection surgery were retrospectively analyzed. The Node-RADS score and short-axis diameter of size-prioritized LNs and the morphology-prioritized LNs were obtained. The correlations of Node-RADS score to the pN stage, LNM number and lymph node ratio (LNR) were investigated. The performances on assessing pathological lymph node metastasis were compared between Node-RADS score and short-axis diameter. A nomogram combined the Node-RADS score and clinical features was also evaluated.

RESULTS

Node-RADS score showed significant correlation with pN stage, LNM number and LNR (Node-RADS of size-prioritized LN: r = 0.600, 0.592, and 0.606; Node-RADS of morphology-prioritized LN: r = 0.547, 0.538, and 0.527; Node-RADSmax: r = 0.612, 0.604, and 0.610; all p < 0.001). For size-prioritized LN, Node-RADS achieved an AUC of 0.826, significantly superior to short-axis diameter (0.826 vs. 0.743, p = 0.009). For morphology-prioritized LN, Node-RADS exhibited an AUC of 0.758, slightly better than short-axis diameter (0.758 vs. 0.718, p = 0.098). The Node-RADS score of size-prioritized LN was significantly better than that of morphology-prioritized LN (0.826 vs. 0.758, p = 0.038). The nomogram achieved the best diagnostic performance (AUC = 0.861) than all the other assessment methods (p < 0.05).

CONCLUSIONS

The Node-RADS scoring system outperforms the short-axis diameter in predicting lymph node metastasis in RC. Size-prioritized LN demonstrates superior predictive efficacy compared to morphology-prioritized LN. The nomogram combined the Node-RADS score of size-prioritized LN with clinical features exhibits the best diagnostic performance. Moreover, a clear relationship was demonstrated between the Node-RADS score and the quantity-dependent pathological characteristics of LNM.

A Retrospective Multicenter Study of Risk Factors, Stratification, and Prognosis of Lymph Node Metastasis in T1 and T2 Colorectal Cancer

BACKGROUND

The objective of this study was to compare the long-term prognosis of patients with T1 and T2 colorectal cancer (CRC) according to lymph node metastasis (LNM) and to identify risk factors for LNM.

METHODS

We retrospectively reviewed patients who underwent curative resection for T1 or T2 CRC at five University-affiliated hospitals between January 2012 and December 2021. The patients were divided into several groups depending on the presence of LNM or the number of risk factors.

RESULTS

Of the total 765 patients, 87 (11.3%) patients had LNM. These patients had poorer recurrence-free survival (RFS) than patients without LNM (72.6% vs. 88.6%). The multivariable analysis showed that high-grade tumors (p = 0.003), lymphovascular invasion (p < 0.001), and rectal location (p = 0.049) were independent predictors of LNM. When divided into groups according to the number of the three risk factors, the risk of LNM increased from 5.4% (ultralow-risk group; no risk factor) to 60.0% (high-risk group; all three risk factors) and the 5-year RFS rate decreased from 96.3% in the ultralow-risk group to 60% in the high-risk group (p < 0.001).

CONCLUSION

Radical surgery should be considered for T1 and T2 CRC patients with these risk factors.

Prognostic Impact of Lymphatic Invasion, Venous Invasion, Perineural Invasion, and Tumor Budding in Rectal Cancer Treated With Neoadjuvant Chemoradiotherapy Followed by Total Mesorectal Excision

BACKGROUND

The diagnostic implications of lymphatic invasion, venous invasion, perineural invasion, and tumor budding in rectal cancer treated with neoadjuvant chemoradiotherapy are unknown.

OBJECTIVE

This study aimed to identify the prognostic impact of lymphatic invasion, venous invasion, perineural invasion, and tumor budding in locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy.

DESIGN

This was a retrospective cohort study.

SETTINGS

This study was conducted at the Samsung Medical Center. Grouping was performed on the basis of lymphatic invasion, venous invasion, perineural invasion, and tumor budding status: no-risk group with 0 factor (n = 299), low-risk group with any 1 factor (n = 131), intermediate-risk group with any 2 factors (n = 75), and high-risk group with 3 or 4 risk factors (n = 32).

PATIENTS

Patients who underwent neoadjuvant chemoradiotherapy, followed by radical operation for locally advanced rectal cancer, from January 2010 to December 2015 were included.

MAIN OUTCOME MEASURES

The main outcome measures were disease-free and overall survival.

RESULTS

Disease-free and overall survival varied significantly between the groups in stage III ( p < 0.001 and p < 0.001). Disease-free survival in stage I differed between the no-risk group and the intermediate-risk group ( p = 0.026). In stage II, disease-free and overall survival differed between the no-risk group and the intermediate-risk group ( p = 0.010 and p = 0.045). In multivariable analysis, risk grouping was an independent prognostic factor for both disease-free (p <0.001) and overall survival ( p < 0.001).

LIMITATIONS

The inherent limitations are associated with the retrospective single-center study design.

CONCLUSIONS

Lymphatic invasion, venous invasion, perineural invasion, and tumor budding are strong prognostic factors for disease-free and overall survival in locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy. Therefore, adjuvant chemotherapy is strongly recommended in patients with positive lymphatic invasion, venous invasion, perineural invasion, and tumor budding. See Video Abstract at http://links.lww.com/DCR/B919 .

IMPACTO PRONSTICO DE LA INVASIN LINFTICA, LA INVASIN VENOSA, LA INVASIN PERINEURAL Y LA GEMACIN TUMORAL EN EL CNCER DE RECTO TRATADO CON QUIMIORRADIOTERAPIA NEOADYUVANTE SEGUIDA DE ESCISIN TOTAL DEL MESORRECTO

ANTECEDENTES:Se desconocen las implicaciones diagnósticas de la invasión linfática, la invasión venosa, la invasión perineural y el crecimiento tumoral en el cáncer de recto tratado con quimiorradioterapia neoadyuvante.OBJETIVO:Este estudio fue diseñado para identificar el impacto pronóstico de la invasión linfática, la invasión venosa, la invasión perineural y la gemación tumoral en el cáncer de recto localmente avanzado tratado con quimiorradioterapia neoadyuvante.DISEÑO:Este estudio fue un estudio de cohorte retrospectivo.AJUSTES:Este estudio se realizó en el Centro Médico Samsung. La agrupación se realizó en función de la invasión linfática, la invasión venosa, la invasión perineural y el estado de crecimiento del tumor: grupo sin riesgo con 0 factores (n = 299), grupo de bajo riesgo con cualquier factor 1 (n = 131), grupo de riesgo intermedio con 2 factores cualquiera (n = 75), y un grupo de alto riesgo con 3 o 4 factores de riesgo (n = 32).PACIENTES:Se incluyeron un total de 537 pacientes que se sometieron a quimiorradioterapia neoadyuvante seguida de operación radical por cáncer de recto localmente avanzado desde enero de 2010 hasta diciembre de 2015.PRINCIPALES MEDIDAS DE RESULTADO:Las principales medidas de resultado fueron la supervivencia libre de enfermedad y la supervivencia general.RESULTADOS:La mediana del período de seguimiento fue de 77 meses, y la supervivencia libre de enfermedad a los 5 años y la supervivencia general a los 5 años variaron significativamente entre los grupos en el estadio III (p < 0,001, p < 0,001). La supervivencia libre de enfermedad a los 5 años en el estadio I difirió entre el grupo sin riesgo y el grupo de riesgo intermedio (p = 0,026). En el estadio II, la supervivencia libre de enfermedad a 5 años y la supervivencia global a 5 años difirieron entre el grupo sin riesgo y el grupo de riesgo intermedio p = 0,010, p = 0,045). En el análisis multivariable, la agrupación de riesgo fue un factor pronóstico independiente tanto para la supervivencia libre de enfermedad (p < 0,001) como para la supervivencia global (p < 0,001).LIMITACIÓN:Las limitaciones inherentes están asociadas con el diseño de estudio retrospectivo de un solo centro..CONCLUSIÓN:La invasión linfática, la invasión venosa, la invasión perineural y la gemación tumoral son fuertes factores pronósticos para la supervivencia libre de enfermedad y la supervivencia general en el cáncer de recto localmente avanzado tratado con quimiorradioterapia neoadyuvante. Por lo tanto, se recomienda fuertemente la quimioterapia adyuvante en pacientes con invasión linfática positiva, invasión venosa, invasión perineural y tumor en en formacion. Consulte Video Resumen en http://links.lww.com/DCR/B919 . (Traducción-Dr Yolanda Colorado ).

Long-term outcomes after endoscopic versus surgical resection of T1 colorectal carcinoma

BACKGROUND

The long-term outcomes of patients with T1 colorectal cancer (CRC) who undergo endoscopic and/or surgical treatment are not well understood. Invasive CRC confined to the colonic submucosa (T1 CRC) is challenging in terms of clinical decision-making. We compared the long-term outcomes of T1 CRC by treatment method.

METHODS

We examined 370 patients with pathological T1 CRC treated between 2000 and 2015 at Seoul St. Mary's Hospital. In total, 93 patients underwent endoscopic resection (ER) only, 82 underwent additional surgery after ER, and 175 underwent surgical resection only. Patients who did not meet the curative criteria were defined as "high-risk." High-risk patients were classified into three groups according to the treatment modalities: ER only (Group A: 35 patients), additional surgery after ER (Group B: 72 patients), and surgical resection only (Group C: 133 patients). The recurrence-free and overall survival (OS) rates, and factors associated with recurrence and mortality, were analyzed. Factors associated with lymph node metastasis (LNM) were subjected to multivariate analysis.

RESULTS

Of the 370 patients, 7 experienced recurrence and 7 died. All recurrences occurred in the high-risk group and two deaths were in the low-risk group. In high-risk groups, there was no significant group difference in recurrence-free survival (P = 0.511) or OS (P =0.657). Poor histology (P =0.042) was associated with recurrence, and vascular invasion (P =0.044) with mortality. LNMs were observed in 30 of 277 patients who underwent surgery either initially or secondarily. Lymphatic invasion was significantly associated with the incidence of LNM (P < 0.001).

CONCLUSIONS

ER prior to surgery did not affect the prognosis of high-risk T1 CRC patients, and did not worsen the clinical outcomes of patients who required additional surgery. Lymphatic invasion was the most important predictor of LNM.

MRI-based multiregional radiomics for predicting lymph nodes status and prognosis in patients with resectable rectal cancer

Purpose

To establish and evaluate multiregional T2-weighted imaging (T2WI)-based clinical-radiomics model for predicting lymph node metastasis (LNM) and prognosis in patients with resectable rectal cancer.

Methods

A total of 346 patients with pathologically confirmed rectal cancer from two hospitals between January 2019 and December 2021 were prospectively enrolled. Intra- and peritumoral features were extracted separately, and least absolute shrinkage and selection operator regression was applied for feature selection. Radiomics signatures were built using the selected features from different regions. The clinical-radiomic nomogram was developed by combining the intratumoral and peritumoral radiomics signatures score (radscore) and the most predictive clinical parameters. The diagnostic performances of the nomogram and clinical model were evaluated using the area under the receiver operating characteristic curve (AUC). The prognostic model for 3-year recurrence-free survival (RFS) was constructed using univariate and multivariate Cox analysis.

Results

The intratumoral radscore (radscore 1) included four features, the peritumoral radscore (radscore 2) included five features, and the combined intratumoral and peritumoural radscore (radscore 3) included ten features. The AUCs for radscore 3 were higher than that of radscore 1 in training cohort (0.77 vs. 0.71, P=0.182) and internal validation cohort (0.76 vs. 0.64, P=0.041). The AUCs for radscore 3 were higher than that of radscore 2 in training cohort (0.77 vs. 0.74, P=0.215) and internal validation cohort (0.76 vs. 0.68, P=0.083). A clinical-radiomic nomogram showed a higher AUC compared with the clinical model in training cohort (0.84 vs. 0.67, P<0.001) and internal validation cohort (0.78 vs. 0.64, P=0.038) but not in external validation (0.72 vs. 0.76, P=0.164). Multivariate Cox analysis showed MRI-reported extramural vascular invasion (EMVI) (HR=1.099, 95%CI: 0.462-2.616; P=0.031) and clinical-radiomic nomogram-based LNM (HR=2.232, 95%CI:1.238-7.439; P=0.017) were independent risk factors for assessing 3-year RFS. Combined clinical-radiomic nomogram based LNM and MRI-reported EMVI showed good performance in training cohort (AUC=0.748), internal validation cohort (AUC=0.706) and external validation (AUC=0.688) for predicting 3-year RFS.

Conclusion

A clinical-radiomics nomogram exhibits good performance for predicting preoperative LNM. Combined clinical-radiomic nomogram based LNM and MRI-reported EMVI showed clinical potential for assessing 3-year RFS.

Establishment and validation of nomograms for predicting mesorectal lymph node staging and restaging

BACKGROUND

Preoperative determination of lymph node (LN) status is crucial in treatment planning for rectal cancer. This study prospectively evaluated the risk factors for lymph node metastasis (LNM) at staging and restaging based on a node-by-node pairing between MRI imaging findings and histopathology and constructed nomograms to evaluate its diagnostic value.

METHODS

From July 2021 to July 2022, patients with histopathologically verified rectal cancer who underwent MRI before surgery were prospectively enrolled. Histological examination of each LN status in the surgical specimens and anatomical matching with preoperative imaging. Taking histopathological results as the gold standard, federating clinical features from patients and LN imaging features on MRI-T2WI. Risk factors for LN metastasis were identified by multivariate logistic regression analysis and used to create a nomogram. The performance of the nomograms was assessed with calibration plots and bootstrapped-concordance index and validated using validation cohorts.

RESULTS

A total of 500 target LNs in 120 patients were successfully matched with node-by-node comparisons. A total of 353 LNs did not receive neoadjuvant therapy and 147 LNs received neoadjuvant chemoradiotherapy (neoCRT). Characterization of LNs not receiving neoadjuvant therapy and multivariate regression showed that the short diameter, preoperative CEA level, mrT-stage, border contour, and signal intensity were associated with a high risk of LN metastasis (P < 0.05). The nomogram predicted that the area under the curve was 0.855 (95% CI, 0.794-0.916) and 0.854 (95% CI, 0.727-0.980) in the training and validation cohorts, respectively. In the neoadjuvant therapy group, short diameter, ymrT-stage, internal signal, and MRI-EMVI were associated with LN positivity (P < 0.05), and the area under the curves using the nomogram was 0.912 (95% CI, 0.856-0.968) and 0.915 (95% CI, 0.817-1.000) in two cohorts. The calibration curves demonstrate good agreement between the predicted and actual probabilities for both the training and validation cohorts.

CONCLUSION

Our nomograms combined with preoperative clinical and imaging biomarkers have the potential to improve the prediction of nodal involvement, which can be used as an essential reference for preoperative N staging and restaging of rectal cancer.

Lymph node regression grading of locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy

Neoadjuvant chemoradiotherapy (nCRT) and total rectal mesenteric excision are the main standards of treatment for locally advanced rectal cancer (LARC). Lymph node regression grade (LRG) is an indicator of prognosis and response to preoperative nCRT based on postsurgical metastatic lymph node pathology. Common histopathological findings in metastatic lymph nodes after nCRT include necrosis, hemorrhage, nodular fibrosis, foamy histiocytes, cystic cell reactions, areas of hyalinosis, residual cancer cells, and pools of mucin. A number of LRG systems designed to classify the amount of lymph node regression after nCRT is mainly concerned with the relationship between residual cancer cells and regressive fibrosis and with estimating the number of lymph nodes existing with residual cancer cells. LRG offers significant prognostic information, and in most cases, LRG after nCRT correlates with patient outcomes. In this review, we describe the systematic classification of LRG after nCRT, patient prognosis, the correlation with tumor regression grade, and the typical histopathological findings of lymph nodes. This work may serve as a reference to help predict the clinical complete response and determine lymph node regression in patients based on preservation strategies, allowing for the formulation of more accurate treatment strategies for LARC patients, which has important clinical significance and scientific value.

Composite scoring system and optimal tumor budding cut-off number for estimating lymph node metastasis in submucosal colorectal cancer

BACKGROUND

Tumor budding is associated with lymph node (LN) metastasis in submucosal colorectal cancer (CRC). However, the rate of LN metastasis associated with the number of tumor buds is unknown. Here, we determined the optimal tumor budding cut-off number and developed a composite scoring system (CSS) for estimating LN metastasis of submucosal CRC.

METHODS

In total, 395 patients with histologically confirmed T1N0-2M0 CRC were evaluated. The clinicopathological characteristics were subjected to univariate and multivariate analyses. The Akaike information criterion (AIC) values of the multivariate models were evaluated to identify the optimal cut-off number. A CSS for LN metastasis was developed using independent risk factors.

RESULTS

The prevalence of LN metastasis was 13.2%. Histological differentiation, lymphatic or venous invasion, and tumor budding were associated with LN metastasis in univariate analyses. In multivariate models adjusted for histological differentiation and lymphatic or venous invasion, the AIC value was lowest for five tumor buds. Unfavorable differentiation (odds ratio [OR], 8.16; 95% confidence interval [CI], 1.80-36.89), lymphatic or venous invasion (OR, 5.91; 95% CI, 2.91-11.97), and five or more tumor buds (OR, 3.01; 95% CI, 1.21-7.69) were independent risk factors. In a CSS using these three risk factors, the rates of LN metastasis were 5.6%, 15.5%, 31.0%, and 52.4% for total composite scores of 0, 1, 2, and ≥ 3, respectively.

CONCLUSIONS

For the estimation of LN metastasis in submucosal CRC, the optimal tumor budding cut-off number was five. Our CSS can be utilized to estimate LN metastasis.

Efficacy of PET/CT in diagnosis of regional lymph node metastases in patients with colorectal cancer: retrospective cohort study

Background

Endoscopic and transanal local resection without lymph node dissection are treatment options for patients with a low risk of lymph node metastasis; however, some patients might have undiagnosed lymph node metastases before surgery. This retrospective study aimed to evaluate the efficacy of preoperative PET/CT for diagnosing regional lymph node metastasis.

Methods

Patients who underwent curative resection with lymph node dissection for colorectal cancer at Osaka University between January 2012 and December 2015 were included. The cut-off values appropriate for diagnosing lymph node metastasis were calculated by way of a receiver operating characteristic (ROC) curves from maximum standard unit value (SUVmax) of main tumour, and lymph node short axis, and SUVmax of lymph node. The cut-off values of primary tumour SUVmax: 7, short-axis diameter of the lymph node at 7 mm, and lymph node SUVmax at 1.5 were set.

Result

A total of 541 patients were included. Regional lymph node metastases were confirmed in resected specimens from 187 patients (35 per cent). With a primary tumour SUVmax of 7 used as a cut-off value, the sensitivity and specificity of regional lymph node metastasis were 70.1 per cent and 45.5 per cent respectively. With a cut-off short-axis diameter of the regional lymph node of 7 mm, the sensitivity and specificity of regional lymph node metastasis were 75.2 per cent and 82.6 per cent respectively, and with a cut-off regional lymph node SUVmax of 1.5, the sensitivity and specificity of regional lymph node metastasis were 78.6 per cent and 96.8 per cent respectively. When the diagnostic criteria were defined by a lymph node short-axis diameter of 7 mm or SUVmax of 1.5, the sensitivity and specificity were 87.4 per cent and 81.8 per cent respectively.

Conclusion

Preoperative PET/CT is a useful modality for evaluating regional lymph node metastasis in patients with colorectal cancer.

Clinico-Radiologic Nomogram Using Multiphase CT to Predict Lymph Node Metastasis in Colon Cancer

PURPOSE

To evaluate the value of multiphase computed tomography (CT)-based radiomics for predicting lymph node metastasis in patients with colorectal cancer (CRC).

METHODS

This study included 191 patients enrolled in our hospital who underwent non-contrast, arterial, and portal venous phase CT scans between June 2017 and December 2019. Segmented regions of interest in each slice of CT images were used to extract radiomics features. Redundant features were ruled out using the least absolute shrinkage and selection operator (LASSO) regression. The multiphase CT-combined radiomics signature (Com-RS) was constructed based on the selected radiomics features from the three CT phases weighted by the respective LASSO coefficients. The nomogram was created by combining the Com-RS with key clinical parameters. The performance of the nomogram was evaluated using receiver operating characteristics, calibration, and decision curve analyses (DCA).

RESULTS

Nine features were demonstrated to be the most significant and used to build the Com-RS: two from non-contrast CT, four from arterial CT, and three from portal venous CT. Tumor length has been identified as a key clinical parameter. A radiomics nomogram was constructed by integrating the Com-RS with tumor length and generated good performance with areas under the curve of 0.830 (95% confidence interval [CI], 0.758 - 0.902) and 0.712 (95% CI, 0.585 - 0.839) in the training and validation cohorts, respectively. Calibration and DCA confirmed the potential clinical relevance and applicability of the nomogram.

CONCLUSIONS

The developed multiphase CT-based radiomics nomogram can potentially serve as an effective tool for the preoperative prediction of lymph node status in CRC.

A model of multiple tumor marker for lymph node metastasis assessment in colorectal cancer: a retrospective study

Background

Assessment of colorectal cancer (CRC) lymph node metastasis (LNM) is critical to the decision of surgery, prognosis, and therapy strategy. In this study, we aimed to develop and validate a multiple tumor marker nomogram for predicting LNM in CRC patients.

Methods

A total of 674 patients who met the inclusion criteria were collected and randomly divided into primary cohort and internal test cohort at a ratio of 7:3. An external test cohort enrolled 178 CRC patients from the West China Hospital. Clinicopathologic variables were obtained from electronic medical records. The least absolute shrinkage and selection operator (LASSO) and interquartile range analysis were carried out for variable dimensionality reduction and feature selection. Multivariate logistic regression analysis was conducted to develop predictive models of LNM. The performance of the established models was evaluated by the receiver operating characteristic (ROC) curve, calibration belt, and clinical usefulness.

Results

Based on minimum criteria, 18 potential features were reduced to six predictors by LASSO and interquartile range in the primary cohort. The model demonstrated good discrimination and ROC curve (AUC = 0.721 in the internal test cohort, AUC = 0.758 in the external test cohort) in LNM assessment. Good calibration was shown for the probability of CRC LNM in the internal and external test cohorts. Decision curve analysis illustrated that multi-tumor markers nomogram was clinically useful.

Conclusions

The study proposed a reliable nomogram that could be efficiently and conveniently utilized to facilitate the assessment of individually-tailored LNM in patients with CRC, complementing imaging and biopsy tests.

The Role of Transanal Endoscopic Surgery for Early Rectal Cancer

Transanal endoscopic surgery (TES), which is performed through a variety of transanal endoluminal multitasking surgical platforms, was developed to facilitate endoscopic en bloc excision of rectal lesions as a minimally invasive alternative to radical proctectomy. Although the oncologic safety of TES in the treatment of malignant rectal tumors has been an area of vigorous controversy over the past two decades, TES is currently accepted as an oncologically safe approach for the treatment of carefully selected early and superficial rectal cancers. TES can also serve as both a diagnostic and potentially curative treatment of partially resected unsuspected malignant polyps. In this article, indications and contraindications for transanal endoscopic excision of early rectal cancer lesions are reviewed, as well as selection criteria for the most appropriate transanal excisional approach. Preoperative preparation and surgical technique for complications of TES will be reviewed, as well as recommended surveillance and management of upstaged tumors.

A Comprehensive Nomogram Combining CT Imaging with Clinical Features for Prediction of Lymph Node Metastasis in Stage I-IIIB Non-small Cell Lung Cancer

OBJECTIVE

The status of lymph node metastasis (LNM) is highly correlated with the recurrence and survival outcomes of patients with lung cancer. Thus, a tool that predicts LNM could benefit patient treatment and prognosis. The present study established a new radiomic model by combining computed tomography (CT) radiomic features and clinical parameters to predict the LNM status in patients with non-small cell lung cancer (NSCLC).

METHODS

Demographic parameters and clinical laboratory values were analyzed in 217 patients with stage I-IIIB NSCLC; 107 of the patients received CT scanning and radiomic characteristics were used for LNM assessment (76 in the training cohort and 31 in the validation cohort). The minimum redundancy maximum relevance (mRMR) and the least absolute shrinkage and selection operator (LASSO) regression model were used to select the most predictive features on the basis of the 76 patients in the training set. The value of the area under the receiver operator characteristic (ROC) curve (AUC) was adopted to determine the correlation between LN status and the radiomics signature in training cohorts and then validated in the 31 patients of validation set. The radiomics nomogram was analyzed using univariate and multivariate logistic regression. Decision curve analysis (DCA) was performed to evaluate the clinical utility of this model.

RESULTS

This was a retrospective study. Five radiomic characteristics were significantly correlated with LNM in the two cohorts (P < 0.05). The radiomic nomogram that incorporated the above radiomic characteristics, the RDW, and the CT-based LN status had satisfactory discrimination and calibration in the training (AUC, 0.79; 95% CI 0.69-0.89) and validation cohorts (AUC, 0.70; 95% CI 0.50-0.89).The DCA showed that the developed nomogram had promising clinical utility.

CONCLUSIONS

The developed nomogram, combined with preoperative radiomics evidence, the RDW, and the CT-based LN status, has the potential to preoperatively predict LNM with high accuracy and can facilitate the prediction of LN status for NSCLC patients.

Development of a Nomogram Combining Clinical Risk Factors and Dual-Energy Spectral CT Parameters for the Preoperative Prediction of Lymph Node Metastasis in Patients With Colorectal Cancer

Objective

This study aimed to develop a dual-energy spectral computed tomography (DESCT) nomogram that incorporated both clinical factors and DESCT parameters for individual preoperative prediction of lymph node metastasis (LNM) in patients with colorectal cancer (CRC).

Material and Methods

We retrospectively reviewed 167 pathologically confirmed patients with CRC who underwent enhanced DESCT preoperatively, and these patients were categorized into training (n = 117) and validation cohorts (n = 50). The monochromatic CT value, iodine concentration value (IC), and effective atomic number (Eff-Z) of the primary tumors were measured independently in the arterial phase (AP) and venous phase (VP) by two radiologists. DESCT parameters together with clinical factors were input into the prediction model for predicting LNM in patients with CRC. Logistic regression analyses were performed to screen for significant predictors of LNM, and these predictors were presented as an easy-to-use nomogram. The receiver operating characteristic curve and decision curve analysis (DCA) were used to evaluate the clinical usefulness of the nomogram.

Results

The logistic regression analysis showed that carcinoembryonic antigen, carbohydrate antigen 199, pericolorectal fat invasion, ICAP, ICVP, and Eff-ZVP were independent predictors in the predictive model. Based on these predictors, a quantitative nomogram was developed to predict individual LNM probability. The area under the curve (AUC) values of the nomogram were 0.876 in the training cohort and 0.852 in the validation cohort, respectively. DCA showed that our nomogram has outstanding clinical utility.

Conclusions

This study presents a clinical nomogram that incorporates clinical factors and DESCT parameters and can potentially be used as a clinical tool for individual preoperative prediction of LNM in patients with CRC.

Mechanisms and Clinical Significance of Tumor Lymphatic Invasion

Tumor-associated lymphatic vessels play an important role in tumor progression, mediating lymphatic dissemination of malignant cells to tumor-draining lymph nodes and regulating tumor immunity. An early, necessary step in the lymphatic metastasis cascade is the invasion of lymphatic vessels by tumor cell clusters or single tumor cells. In this review, we discuss our current understanding of the underlying cellular and molecular mechanisms, which include tumor-specific as well as normal, developmental and immunological processes “hijacked” by tumor cells to gain access to the lymphatic system. Furthermore, we summarize the prognostic value of lymphatic invasion, discuss its relationship with local recurrence, lymph node and distant metastasis, and highlight potential therapeutic options and challenges.

Development and validation of a collagen signature-based nomogram for preoperatively predicting lymph node metastasis and prognosis in colorectal cancer

Background

Current preoperative evaluation approaches cannot provide adequate information for the prediction of lymph node (LN) metastasis in colorectal cancer (CRC). Collagen alterations in the tumor microenvironment affect the progression of tumor cells. To more accurately assess the LN status of CRC preoperatively, we developed and validated a collagen signature-based nomogram for predicting LN metastasis in CRC.

Methods

In total, 342 consecutive CRC patients were assigned to the training and validation cohorts. A total of 148 fully quantitative collagen features were extracted based on preoperative biopsies using multiphoton imaging, and the least absolute shrinkage and selection operator method was utilized to construct the collagen signature. A collagen signature-based nomogram was developed by multivariable logistic regression in the training cohort. Nomogram performance was evaluated for its discrimination, calibration, and clinical usefulness and then validated in the validation cohort. The prognostic values of the nomogram were also evaluated.

Results

A seven-feature-based collagen signature was built. We found that the collagen signature showed a significant association with LN metastasis in CRC. Additionally, a nomogram incorporating preoperative tumor differentiation, computed tomography-reported T stage and LN status, carcinoembryonic antigen level, carbohydrate antigen 19-9 level and collagen signature was developed. This nomogram had good discrimination and calibration, with AUROCs of 0.826 and 0.846 in the training and validation cohorts, respectively, and had a sensitivity of 86.5%, a specificity of 68.2%, an accuracy of 76.9%, a negative predictive value of 84.9%, and a positive predictive value of 71.2% for all patients. Compared to the clinicopathological model, which consisted of the clinicopathological risk factors for LN metastasis, the collagen signature-based nomogram demonstrated a significantly improved ability to discriminate LN status. Moreover, a nomogram-predicted high-risk subgroup had remarkably reduced survival compared with that of the low-risk subgroup.

Conclusions

The collagen signature in the tumor microenvironment of preoperative biopsies is an independent predictor for LN metastasis in CRC, and the collagen signature-based nomogram is helpful for tailored treatment and prognostic predictions in CRC preoperatively.

Lymph Node Positivity in T1/T2 Rectal Cancer: a Word of Caution in an Era of Increased Incidence and Changing Biology for Rectal Cancer

BACKGROUND

The evaluation of lymph nodes in rectal cancer dictates treatment. The goals of this study are to characterize the contemporary rate of lymph node metastasis in early stage rectal cancer and to re-investigate histologic factors that predict positive lymph nodes.

MATERIALS AND METHODS

Using the National Cancer Database, we identified patients with clinical stage I rectal adenocarcinoma. Multivariable logistic regression was used to determine risk factors for lymph node positivity.

RESULTS

12.2% of patients with T1 tumors and 18.0% of patients with T2 tumors had positive lymph nodes. For T1 tumors, positive lymph nodes were present in 9.3% with neither poor differentiation nor lymphovascular invasion (LVI), 17.3% with poor differentiation alone, 34.7% with LVI alone, and 45.0% with both poor differentiation and LVI. For T2 tumors, positive lymph nodes were present in 11.7% with neither poor differentiation nor LVI, 25.3% with poor differentiation alone, 47.3% with LVI alone, and 41.5% with both poor differentiation and LVI. LVI was an independent predictor of positive lymph nodes (OR;4.75,95%CI;3.17-7.11,p < 0.001) for T1 and (OR;6.20,95%CI;4.53-8.51,p < 0.001) T2 tumors.

CONCLUSIONS

T1/T2 tumors have higher rates of positive lymph nodes when poor differentiation and LVI are present. These results should be taken into consideration prior to surgical treatment.

Development of a Novel Prognostic Model for Predicting Lymph Node Metastasis in Early Colorectal Cancer: Analysis Based on the Surveillance, Epidemiology, and End Results Database

Background

Identification of a simplified prediction model for lymph node metastasis (LNM) for patients with early colorectal cancer (CRC) is urgently needed to determine treatment and follow-up strategies. Therefore, in this study, we aimed to develop an accurate predictive model for LNM in early CRC.

Methods

We analyzed data from the 2004-2016 Surveillance Epidemiology and End Results database to develop and validate prediction models for LNM. Seven models, namely, logistic regression, XGBoost, k-nearest neighbors, classification and regression trees model, support vector machines, neural network, and random forest (RF) models, were used.

Results

A total of 26,733 patients with a diagnosis of early CRC (T1) were analyzed. The models included 8 independent prognostic variables; age at diagnosis, sex, race, primary site, histologic type, tumor grade, and, tumor size. LNM was significantly more frequent in patients with larger tumors, women, younger patients, and patients with more poorly differentiated tumor. The RF model showed the best predictive performance in comparison to the other method, achieving an accuracy of 96.0%, a sensitivity of 99.7%, a specificity of 92.9%, and an area under the curve of 0.991. Tumor size is the most important features in predicting LNM in early CRC.

Conclusion

We established a simplified reproducible predictive model for LNM in early CRC that could be used to guide treatment decisions. These findings warrant further confirmation in large prospective clinical trials.

Multiregional-Based Magnetic Resonance Imaging Radiomics Combined With Clinical Data Improves Efficacy in Predicting Lymph Node Metastasis of Rectal Cancer

Objective

To develop and validate a multiregional-based magnetic resonance imaging (MRI) radiomics model and combine it with clinical data for individual preoperative prediction of lymph node (LN) metastasis in rectal cancer patients.

Methods

186 rectal adenocarcinoma patients from our retrospective study cohort were randomly selected as the training (n = 123) and testing cohorts (n = 63). Spearman’s rank correlation coefficient and the least absolute shrinkage and selection operator were used for feature selection and dimensionality reduction. Five support vector machine (SVM) classification models were built using selected clinical and semantic variables, single-regional radiomics features, multiregional radiomics features, and combinations, for predicting LN metastasis in rectal cancer. The performance of the five SVM models was evaluated via the area under the receiver operator characteristic curve (AUC), accuracy, sensitivity, and specificity in the testing cohort. Differences in the AUCs among the five models were compared using DeLong’s test.

Results

The clinical, single-regional radiomics and multiregional radiomics models showed moderate predictive performance and diagnostic accuracy in predicting LN metastasis with an AUC of 0.725, 0.702, and 0.736, respectively. A model with improved performance was created by combining clinical data with single-regional radiomics features (AUC = 0.827, (95% CI, 0.711–0.911), P = 0.016). Incorporating clinical data with multiregional radiomics features also improved the performance (AUC = 0.832 (95% CI, 0.717–0.915), P = 0.015).

Conclusion

Multiregional-based MRI radiomics combined with clinical data can improve efficacy in predicting LN metastasis and could be a useful tool to guide surgical decision-making in patients with rectal cancer.

Deep Convolutional Neural Network-Based Lymph Node Metastasis Prediction for Colon Cancer Using Histopathological Images

Background

Human evaluation of pathological slides cannot accurately predict lymph node metastasis (LNM), although accurate prediction is essential to determine treatment and follow-up strategies for colon cancer. We aimed to develop accurate histopathological features for LNM in colon cancer.

Methods

We developed a deep convolutional neural network model to distinguish the cancer tissue component of colon cancer using data from the tissue bank of the National Center for Tumor Diseases and the pathology archive at the University Medical Center Mannheim, Germany. This model was applied to whole-slide pathological images of colon cancer patients from The Cancer Genome Atlas (TCGA). The predictive value of the peri-tumoral stroma (PTS) score for LNM was assessed.

Results

A total of 164 patients with stages I, II, and III colon cancer from TCGA were analyzed. The mean PTS score was 0.380 (± SD = 0.285), and significantly higher PTS scores were observed in patients in the LNM-positive group than those in the LNM-negative group (P < 0.001). In the univariate analyses, the PTS scores for the LNM-positive group were significantly higher than those for the LNM-negative group (P < 0.001). Further, the PTS scores in lymphatic invasion and any one of perineural, lymphatic, or venous invasion were significantly increased in the LNM-positive group (P < 0.001 and P < 0.001).

Conclusion

We established the PTS score, a simplified reproducible parameter, for predicting LNM in colon cancer using computer-based analysis that could be used to guide treatment decisions. These findings warrant further confirmation through large-scale prospective clinical trials.

Molecular Features of Lymph Node Metastasis in T1/2 Colorectal Cancer from Formalin-Fixed Paraffin-Embedded Archival Specimens

Histological risk factors for lymph node metastasis (LNM) in early-stage colorectal cancers (CRC) have been described, although the predictive utility of these factors varies. Improved LNM risk assessment based on findings in endoscopic colon and rectal excisions is necessary for optimal surgical management of CRC patients with pathologic T1- /T2-staged invasive depth (i.e., tumor not invading beyond the muscularis propria layer); as the current system is overly conservative, and results in many unnecessary radical surgeries. To identify molecular features in early CRC with elevated LNM potential, we carried out proteomic and gene expression profiling to compare T1 lymph node (LN) negative with T1/2 LN positive CRC tumors from formalin-fixed paraffin-embedded (FFPE) specimens. Using a data-independent acquisition mass spectrometry workflow, we detected over 7400 proteins and quantified over 4400 in all 21 specimens. Proteins from tumors with LN metastasis were enriched with effectors of epithelial-mesenchymal transition (EMT) and gene expression profiling confirmed activation of key transcription factors, SNAI1 and ZEB1, as well as a reduction in E-cadherin expression. Toward an implementation pathway, we investigated immunohistochemistry assays targeting four EMT-related proteins. While MS could reliably discern twofold protein abundance changes, we found the semiquantitative nature of IHC scoring limited confirmation of this degree of protein expression difference. This study demonstrated that EMT effectors are associated with locoregional metastasis in T1/T2 CRC and could be used to augment metastatic risk assessment, although further developments are required to enable routine implementation.

Immature Stroma and Prognostic Profiling in Colorectal Carcinoma: Development and Validation of Novel Classification Systems

Many pathological characteristics have utility for predicting prognosis in colorectal carcinoma (CRC). Some of the most important include tumor stage (TS), lymph node status (LNS) and tumor budding (TB). Tumor budding is a phenomenon originally described in 1949 as sprouting. TB assessment is not always reliable however, as it is subject to high inter-observer variation. This finding persists despite the current trends for sub-specialty training in surgical pathology. In light of this, new and reproducible histological prognostic markers could change the way we diagnose and manage patients with colorectal carcinoma. Studies have shown that desmoplastic reaction (DR) categorization can actually outperform other conventional prognostic factors, including tumor budding and tumor stage in predicting disease-free survival (DFS). Our study aimed to evaluate and assess the prognostic value of desmoplastic reaction in an American cohort with colorectal cancer using 3 different stromal classification scoring systems. In all three stromal grading systems, immature stroma was the most significant independent prognostic factor in CRC. Currently, none of the reporting protocols for the College of American Pathologists, the Royal College of Pathologists of the United Kingdom, and the Japanese Society for Cancer report on the presence of immature stroma. Importantly, regarding the ability to predict survival outcomes, our novel classification system has the potential to outperform other scoring methodologies.

Development and external validation of a predictive scoring system associated with metastasis of T1-2 colorectal tumors to lymph nodes

BACKGROUND

It is critical for determining the optimum therapeutic solutions for T1-2 colorectal cancer (CRC) to accurately predict lymph node metastasis (LNM) status. The purpose of the present study is to establish and verify a nomogram to predict LNM status in T1-2 CRCs.

METHODS

A total of 16 600 T1-2 CRC patients were enrolled and classified into the training, internal validation, and external validation cohorts. The independent predictive parameters were determined by univariate and multivariate analyses to develop a nomogram to predict the probability of LNM status. The calibration curve, the area under the receiver operating characteristic curve (AUROC), and decision curve analysis (DCA) were used to evaluate the performance of the nomogram, and an external verification cohort was to verify the applicability of the nomogram.

RESULTS

Seven independent predictors of LNM in T1-2 CRC were identified in the multivariable analysis, including age, tumor site, tumor grade, perineural invasion, preoperative carcinoembryonic antigen, clinical assessment of LNM, and T stage. A nomogram incorporating the seven predictors was constructed. The nomogram yielded good discrimination and calibration, with AUROCs of 0.72 (95% confidence interval [CI]: 0.70-0.75), 0.70 (95% CI: 0.67-0.74), and 0.74 (95% CI: 0.71-0.79) in the training, internal validation, and external validation cohorts, respectively. DCA showed that the predictive scoring system had high clinical application value.

CONCLUSIONS

We proposed a novel predictive model for LNM in T1-2 CRC patients to assist physicians in making treatment decisions. The nomogram is advantageous for tailoring therapy in T1-2 CRC patients.

Association of the tumour stroma percentage in the preoperative biopsies with lymph node metastasis in colorectal cancer

BACKGROUND

Preoperative prediction of lymph node (LN) status is integral to determining the most appropriate treatment strategy for colorectal cancer (CRC). This study aimed to develop and validate a nomogram to predict LN metastasis in CRC preoperatively.

METHODS

A total of 530 patients were enrolled and divided into training and validation cohorts. The tumour stroma percentage (TSP) of the preoperative biopsies was assessed. The risk factors for LN metastasis were selected, and a nomogram was constructed subsequently. The performance of the nomogram was assessed by using the AUROC and the calibration curve, and then validated in the validation cohort.

RESULTS

High TSP was significantly associated with LN metastasis in both the training and validation cohorts. Computed tomography (CT)-reported T stage, CT-reported LN status, preoperative tumour differentiation, carcinoembryonic antigen, carbohydrate antigen 19-9 and TSP were independent predictors of LN metastasis in CRC. A nomogram incorporating the six predictors was constructed. The nomogram yielded good discrimination and calibration, with an AUROC of 0.846 (95% CI: 0.807-0.886) and 0.809 (95% CI: 0.745-0.872) in the training and validation cohorts, respectively.

CONCLUSIONS

Assessment of TSP in the preoperative biopsies provided additional information about the LN status. The nomogram was useful for tailored therapy in CRC preoperatively.

Can less be more? Organ preservation strategies in the management of rectal cancer

Background

Total mesorectal excision (tme) is the current standard of care for the treatment of rectal cancer. However, that surgery is associated with significant morbidity and mortality. Clinicians and patients are seeking alternatives to radical resection. Currently, prevalent organ-sparing strategies under investigation include local excision and nonoperative management (nom).

Methods

We reviewed the current evidence in the literature to create an overview of the use of transanal endoscopic surgery and watch-and-wait strategies in the modern management of rectal cancer.

Results

Compared with radical resection, transanal endoscopic surgery in patients with early rectal cancer (cT1) having favourable histopathologic features is associated with an increased risk of local recurrence, but no difference in 5-year survival. In patients with T2 or early T3 cancer, strategies that use neoadjuvant or adjuvant therapy as adjuncts to local excision are under evaluation. Nonoperative management is a new option for patients who experience a complete clinical response after neoadjuvant chemoradiotherapy (ncrt). The selection criteria that will appropriately identify patients for whom nom will succeed are not established.

Conclusions

Local excision is appropriate for early rectal cancer with favourable histopathologic features. Although organ-preserving strategies are promising, the quality of the evidence to date is insufficient to replace the current standard care in most patients. Patients should be offered nom in the safe setting of a clinical trial or registry. Rigorous follow-up, including endoscopy and imaging at frequent intervals is recommended when radical resection is forgone.

Preoperative assessment of lymph node metastasis in clinically node-negative rectal cancer patients based on a nomogram consisting of five clinical factors

Background

Currently, reliable approaches for accurate assessment of lymph node metastases (LNM), which is an important indication of preoperative chemoradiotherapy (CRT), are not available for clinically node-negative rectal cancer patients. This study aims to identify clinical factors associated with LNM and to establish a nomogram for LNM prediction in clinically node-negative rectal cancer patients.

Methods

The least absolute shrinkage and selection operator (LASSO) aggression and multivariate logistic regression analyses were applied to identify clinical factors associated with LNM. A nomogram was established to predict the probability of LNM in clinically node-negative rectal cancer patients based on the multivariate logistic regression model.

Results

Six potential risk factors were selected on the basis of LASSO aggression analysis, and five of them were identified as independent risk factors for LNM based on multivariate analysis, including MRI-reported tumor location, clinical T classification, MRI-reported tumor diameter, white blood cell count (WBC), and preoperative elevated tumor markers. A nomogram consisting of the five clinical factors was established and showed good discrimination. Decision curve analysis demonstrated that the established nomogram was reliable and accurate for LNM prediction in clinically node-negative rectal cancer patients.

Conclusions

A nomogram based on five clinical factors, including MRI-reported tumor location, clinical T classification, MRI-reported tumor diameter, WBC, and preoperative elevated tumor markers, are useful for assessing LNM in clinically node-negative rectal cancer patients, which is important for preoperative CRT regimens.

Young age increases the risk for lymph node metastasis in patients with early Colon Cancer

Background

The risk of lymph node positivity in early-stage colon cancer is a parameter that impacts therapeutic recommendations. However, little is known about the effect of age on lymph node positivity in colon cancer with mucosal invasion. In this study, we aimed to quantify the effect of younger age on lymph node positivity in colon cancer with mucosal invasion.

Methods

All patients were identified between 2004 and 2014 in the Surveillance, Epidemiology, and End Results database. Patients were stage T1-T2, did not undergo preoperative radiotherapy, had at least one lymph node examined, and underwent a standard colon cancer operation. Demographics and pathological data were compared between different age ranges. A nomogram model was built to estimate the probability of nodal involvement according to different characteristics. Decision curve analysis was performed by calculating the net benefits for a range of threshold probabilities.

Results

This study identified 41,490 patients who met the eligibility criteria for our study. 1.4% (n = 620) of patients were under 40 years old; 5.9% (n = 2571) were between 40 and 49 years old. Within each T stage, positive lymph node rates decreased with increasing age. In univariate analyses, the positive lymph node rates for patients 20 to 39 years of age were significantly higher than in patients in the reference group for stages T1 and T2. After dividing the colon into the left and right parts, these trends remained. The lymph node metastatic rate was higher in the right colon than in the left colon in terms of different age ranges. The nomogram prediction system represents a novel model with which to estimate lymph node metastasis in early T stage colon adenocarcinomas based on four risk factors with a C-index of 0.657 (95% CI: 0.658–0666).

Conclusions

Our study demonstrates that the risk of lymph node metastasis was higher in young (< 40 years) patients with early-stage colon adenocarcinomas. Therefore, more aggressive screening and therapeutic strategies should be considered for young patients with colon adenocarcinoma.

Pathological risk factors and predictive endoscopic factors for lymph node metastasis of T1 colorectal cancer: a single-center study of 846 lesions

BACKGROUND

Determining the depth of invasion of early stage colorectal cancer has been emphasized as a means of improving endoscopic diagnostic accuracy. Recent studies have focused on other pathological risk factors for lymph node metastasis (LNM). We investigated the significance of depth of invasion and predictive properties of other endoscopic findings.

METHODS

We retrospectively investigated 846 patients with submucosal invasive (T1) colorectal cancer who received an accurate pathological diagnosis and were treated between January 2005 and December 2016. Pathological risk factors associated with LNM were reviewed. We divided patients into groups: low-risk T1 colorectal cancer (LRC; no risk factors) and high-risk T1 colorectal cancer (HRC; exhibiting lymphovascular invasion, tumor budding grade of 2/3, and/or poor differentiation) and studied predictive endoscopic factors for HRC.

RESULTS

Significant risk factors for LNM in multivariate analysis were lymphovascular invasion [odds ratio (OR) 8.09; 95% confidence interval (CI) 3.84-17.1], tumor budding (OR 1.89; 95% CI 1.09-3.29), and histological differentiation (OR 2.09; 95% CI 1.12-3.89). The LNM-positive rate with only deep submucosal invasion was 1.6%. Significant predictive factors for HRC in multivariate analysis identified rectal tumor location (OR 1.92; 95% CI 1.35 -2.72, depression (OR 2.73; 95% CI 1.96 -3.80), protuberance within the depression (OR 2.58; 95% CI 1.39- 4.78), expansiveness (OR 2.39; 95% CI 1.27- 4.50), and loss of mucosal patterns (OR 1.90; 95% CI 1.20 -3.01) as significant factors.

CONCLUSIONS

Rectal tumor location, depression, protuberance within the depression, expansiveness, and loss of mucosal patterns could be predictive factors for HRC.

Tumor Budding in Colorectal Carcinoma: Translating a Morphologic Score Into Clinically Meaningful Results

CONTEXT

- Tumor budding has received increasing recognition as an important independent prognostic factor in colorectal carcinoma. Prominent tumor budding in adenocarcinoma arising in a polyp has been shown to be a risk factor for lymph node involvement. The variability in methods used for evaluating tumor budding in different studies and lack of standardized guidelines have impeded routine inclusion of tumor budding in pathology reports. This changed last year with consensus guidelines based on the International Tumor Budding Consensus Conference (ITBCC). These guidelines have been included in the recent College of American Pathologists (CAPs) Colorectal Cancer Protocol. The consensus methodology will allow uniform reporting of this finding, but challenges in interpretation in the setting of intense inflammation, fibrosis, or gland fragmentation need to be addressed in future guidelines.

OBJECTIVE

- To provide a brief overview of the known clinical significance of tumor budding in colorectal carcinoma and discuss the practical aspects of its implementation on a routine basis.

DATA SOURCES

- English-language pathology literature.

CONCLUSIONS

- Tumor budding has been shown to be an independent prognostic marker in colorectal carcinomas and the routine reporting of tumor buds is now advocated by using the approach outlined by the ITBCC guidelines. Tumor budding is included in the CAP protocol as a recommended element. Presence of prominent tumor budding in an adenocarcinoma in a polyp may have implications for management, such as additional resection, while it serves as a prognostic factor in other settings.

Predicting systemic spread in early colorectal cancer: Can we do better?

Through the implementation of national bowel cancer screening programmes we have seen a three-fold increase in early pT1 colorectal cancers, but how these lesions should be managed is currently unclear. Local excision can be an attractive option, especially for fragile patients with multiple comorbidities, but it is only safe from an oncological point of view in the absence of lymph node metastasis. Patient risk stratification through careful analysis of histopathological features in local excision or polypectomy specimens should be performed according to national guidelines to avoid under- or over-treatment. Currently national guidelines vary in their recommendations as to which factors should be routinely reported and there is no established multivariate risk stratification model to determine which patients should be offered major resectional surgery. Conventional histopathological parameters such as tumour grading or lymphovascular invasion have been shown to be predictive of lymph node metastasis in a number of studies but the inter- and intra-observer variation in reporting is high. Newer parameters including tumour budding and poorly differentiated clusters have been shown to have great potential, but again some improvement in the inter-observer variation is required. With the implementation of digital pathology into clinical practice, quantitative parameters like depth/area of submucosal invasion and proportion of stroma can be routinely assessed. In this review we present the various histopathological risk factors for predicting systemic spread in pT1 colorectal cancer and introduce potential novel quantitative variables and multivariable risk models that could be used to better define the optimal treatment of this increasingly common disease.

Incidence, risk factors, and a predictive model for lymph node metastasis of submucosal (T1) colon cancer: A population-based study

OBJECTIVE

This study aimed to assess the incidence, identify independent factors, and develop a lymph node metastasis (LNM) prediction model for patients with T1 colon cancer.

METHODS

Statistics were drawn from the Surveillance, Epidemiology, and End Results database between 2004 and 2014. A multivariate logistic regression analysis was performed to determine independent predictors of LNM. A nomogram for predicting the possibility of LNM was developed based on those factors.

RESULTS

A total of 5397 patients with T1 colon cancer were identified. The overall LNM rate was 15.0% (808/5397). A multivariate analysis showed that age (odds ratio [OR] 0.97, P < 0.001), tumor size (OR 1.01, P < 0.001), moderate (OR 1.77, P = 0.001) or poorly differentiated/undifferentiated tumor (OR 5.60, P < 0.001), right colon cancer (OR 1.39, P = 0.008), and a positive carcinoembryonic antigen level (OR 1.51, P = 0.004) were independent predictive factors for LNM. The area under the receiver operating characteristic curve was 0.68 (95% confidence interval [CI] 0.65-0.71) in the training set and 0.65 (95% CI 0.61-0.67) in the validation set. A calibration plot showed good consistency between the bias-corrected prediction and the ideal reference line with 1000 additional bootstraps (mean absolute error = 0.007).

CONCLUSIONS

The incidence of LNM was high in patients with T1 colon cancer. A nomogram for predicting the probability of LNM for T1 colon cancer may be used to help determine the optimal treatment for these patients.

Impact of Age on Risk of Lymph Node Positivity in Patients with Colon Cancer

Background: Lymph node (LN) positivity is a prognostic indicator in patients with colon cancer regardless of age, and age is an important parameter that impacts therapeutic recommendations. But little is known about the impact of age on LN positivity in patients with colon cancer. Methods: We analyzed 257,334 patients with colon cancer diagnosed from SEER database. Logistic regression was used to examine the association of age and LN positivity. Poisson regression was used to evaluate whether age was associated with the number of positive LNs. Results: LN positivity was inversely associated with age (P < .001 for each T stage). Age was predictive of LN positivity after adjustment for number of LNs examined and other covariates (P < .001 for each T stage). Adjusted odds ratios (ORs) for LN positivity for age 20 to 39 vs 80+ were 3.06 for stage T1 (95 % CI, 2.09 to 4.48), 2.46 for stage T2 (95 % CI, 2.00 to 3.02), 1.77 for stage T3 (95 % CI, 1.62 to 1.93), and 1.68 for stage T4 (1.51 to 1.86). Young age was a significant predictor of an increased number of positive LNs (P < .005 for each T stage). Conclusion: Young age at diagnosis is associated with an increased risk of LN positivity. LN examination and resection could aid younger patients more with detection and removal of metastasis. Guidelines that define postdetection interventions may be needed to limit the overtreatment of older patients, who may be vulnerable to unnecessary tests and treatments.

Predictive Value of [18F]FDG PET/CT for Lymph Node Metastasis in Rectal Cancer

[¹⁸F]Fluorodeoxyglucose ([¹⁸F]FDG) Positron emission tomography/computed tomography (PET/CT) is commonly used for rectal cancer staging, but improved diagnostic methods for nodal metastases are needed. We aimed to evaluate whether the combination model of the metabolic tumor volume of primary tumor (T_MTV) and maximum standardized uptake value of lymph node (N_SUVmax) on pretreatment [¹⁸F]FDG PET/CT could improve nodal metastases prediction in rectal cancer. We enrolled a total of 166 rectal cancer patients who underwent pretreatment [¹⁸F]FDG PET/CT and surgical resection without neoadjuvant treatment between January 2009 and August 2016. Visual and semiquantitative PET/CT parameters were obtained. Associations between clinicopathological, PET/CT-derived variables and nodal metastases were evaluated by logistic regression analysis. Nodal metastases were confirmed histologically in 68 of the 166 patients (41%). Uni- and multivariate analyses demonstrated T_MTV and N_SUVmax were independent predictive factors for nodal metastases. The c-statistics of the combination model was 0.806 (Standard Error, 0.034; 95% Confidence Interval, 0.737-0.863), which showed significant improvement compared to T_MTV (0.698, P = 0.0002) or N_SUVmax (0.720, P = 0.0008) alone. T_MTV and N_SUVmax are independently correlated with nodal metastases. Furthermore, the combination model showed improved performance for risk prediction; thus, [¹⁸F]FDG PET/CT might have a role in rectal cancer staging and treatment planning.

The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges

Medical imaging can assess the tumor and its environment in their entirety, which makes it suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in computational methods, especially in artificial intelligence for medical image process and analysis, has converted these images into quantitative and minable data associated with clinical events in oncology management. This concept was first described as radiomics in 2012. Since then, computer scientists, radiologists, and oncologists have gravitated towards this new tool and exploited advanced methodologies to mine the information behind medical images. On the basis of a great quantity of radiographic images and novel computational technologies, researchers developed and validated radiomic models that may improve the accuracy of diagnoses and therapy response assessments. Here, we review the recent methodological developments in radiomics, including data acquisition, tumor segmentation, feature extraction, and modelling, as well as the rapidly developing deep learning technology. Moreover, we outline the main applications of radiomics in diagnosis, treatment planning and evaluations in the field of oncology with the aim of developing quantitative and personalized medicine. Finally, we discuss the challenges in the field of radiomics and the scope and clinical applicability of these methods.

A Review of Current Challenges in Colorectal Cancer Reporting

Context.—

Pathologic assessment of colorectal cancer resection specimens plays an important role in postsurgical management and prognostication in patients with colorectal cancer. Challenges exist in the evaluation and reporting of these specimens, either because of difficulties in applying existing guidelines or related to newer concepts.

Objective.—

To address challenging areas in colorectal cancer pathology and to provide an overview of the literature, current guidelines, and expert recommendations for the handling of colorectal cancer resection specimens in everyday practice.

Data Sources.—

PubMed (US National Library of Medicine, Bethesda, Maryland) literature review; reporting protocols of the College of American Pathologists, the Royal College of Pathologists of the United Kingdom, and the Japanese Society for Cancer of the Colon and Rectum; and classification manuals of the American Joint Committee on Cancer and the Union for International Cancer Control.

Conclusions.—

This review has addressed issues and challenges affecting quality of colorectal cancer pathology reporting. High-quality pathology reporting is essential for prognostication and management of patients with colorectal cancer.

Predictive Factors for Lymph Node Metastasis in Submucosal Invasive Colorectal Carcinoma: A New Proposal of Depth of Invasion for Radical Surgery

BACKGROUND

Patients with lymph node metastasis (LNM) in submucosal invasive colorectal carcinoma (SM cancer) require additional surgical treatment after endoscopic dissection. However, because additional radical resection after endoscopic local resection may be unnecessary for cases without LNM, more specific criteria are required in order to diminish the incidence of further radical resection after endoscopic dissection.

METHODS

A total of 492 patients with biopsy-proven SM cancer who underwent curative surgery between January 2008 and December 2012 were collected and were divided into LNM group and no LNM group. The cutoff value for the depth of submucosal invasion was analyzed by a receiver operating characteristic (ROC) curve. In this retrospective study, the association between LNM and clinicopathologic factors was analyzed by logistic regression analysis.

RESULTS

The depth of submucosal invasion of 1900 μm was determined as the cutoff value by ROC curve. Significant, independent predictive factors for LNM included the depth of submucosal invasion >1900 μm (odds ratio [OR] 7.5; 95% confidence interval [CI] 3.1-18.3; p < 0.001), venous invasion (OR 2.4; 95% CI 1.1-5.5; p = 0.03), and poorly differentiated/mucinous adenocarcinoma (OR 6.3; 95% CI 1.3-30.8; p = 0.02).

CONCLUSIONS

Our study demonstrates that the depth of submucosal invasion (>1900 μm), vascular invasion and poorly differentiated/mucinous carcinoma were predictive factors of LNM in patients with SM cancer. These predictors may help to reduce the incidence of unnecessary surgery after endoscopic resection.

Management of Pt1 tumours removed by endoscopy during colorectal cancer screening: Outcome and treatment quality indicators

INTRODUCTION

Limited information is available about outcomes of patients with malignant adenomas endoscopically resected at screening. The aim of the study was to evaluate diagnostic and therapeutic quality indicators and to correlate them with clinical and surgical outcomes.

MATERIALS AND METHODS

We reviewed endoscopic and histology characteristics of all pT1 tumours endoscopically removed at the time of colonoscopy assessment in subjects with a positive screening test result in the context of a population-based program.

RESULTS

392 pT1 tumours were completely removed by endoscopy (en-bloc = 86.7%, piecemeal = 13.3%) and the histology report was considered complete in 83.2% of cases. Treatment was limited to endoscopic excision for 120 patients (30.7%, Group 1), 272 (69.3%, Group 2) underwent radicalisation surgery. In patients who had at least 1 lymph node examined, the rate of nodal involvement was 5.4% (13/239); no metastatic node was found in the 21 (27.6%) out of 76 patients with low-risk adenomas, who underwent surgery.

CONCLUSION

Risk of nodal involvement in colorectal pT1 tumours is well predicted by known histologic features also in a screening setting, although it was lower than among patients from clinical series. Surgical overtreatment is still significantly present and there is ample room for improvement regarding diagnostic and therapeutic flow-chart.

Development of a preoperative prediction nomogram for lymph node metastasis in colorectal cancer based on a novel serum miRNA signature and CT scans

BACKGROUND

Preoperative prediction of lymph node (LN) status is of crucial importance for appropriate treatment planning in patients with colorectal cancer (CRC). In this study, we sought to develop and validate a non-invasive nomogram model to preoperatively predict LN metastasis in CRC.

METHODS

Development of the nomogram entailed three subsequent stages with specific patient sets. In the discovery set (n = 20), LN-status-related miRNAs were screened from high-throughput sequencing data of human CRC serum samples. In the training set (n = 218), a miRNA panel-clinicopathologic nomogram was developed by logistic regression analysis for preoperative prediction of LN metastasis. In the validation set (n = 198), we validated the above nomogram with respect to its discrimination, calibration and clinical application.

FINDINGS

Four differently expressed miRNAs (miR-122-5p, miR-146b-5p, miR-186-5p and miR-193a-5p) were identified in the serum samples from CRC patients with and without LN metastasis, which also had regulatory effects on CRC cell migration. The combined miRNA panel could provide higher LN prediction capability compared with computed tomography (CT) scans (P < .0001 in both the training and validation sets). Furthermore, a nomogram integrating the miRNA-based panel and CT-reported LN status was constructed in the training set, which performed well in both the training and validation sets (AUC: 0.913 and 0.883, respectively). Decision curve analysis demonstrated the clinical usefulness of the nomogram.

INTERPRETATION

Our nomogram is a reliable prediction model that can be conveniently and efficiently used to improve the accuracy of preoperative prediction of LN metastasis in patients with CRC.

Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome

Background

Tumor budding, meaning a detachment of tumor cells at the invasion front of colorectal carcinoma (CRC) into single cells or clusters (<=5 tumor cells), has been shown to correlate to an inferior clinical outcome by several independent studies. Therefore, it has been discussed as a complementary prognostic factor to the TNM staging system, and it is already included in national guidelines as an additional prognostic parameter. However, its application by manual evaluation in routine pathology is hampered due to the use of several slightly different assessment systems, a time-consuming manual counting process and a high inter-observer variability. Hence, we established and validated an automatic image processing approach to reliably quantify tumor budding in immunohistochemically (IHC) stained sections of CRC samples.

Methods

This approach combines classical segmentation methods (like morphological operations) and machine learning techniques (k-means and hierarchical clustering, convolutional neural networks) to reliably detect tumor buds in colorectal carcinoma samples immunohistochemically stained for pan-cytokeratin. As a possible application, we tested it on whole-slide images as well as on tissue microarrays (TMA) from a clinically well-annotated CRC cohort.

Results

Our automatic tumor budding evaluation tool detected the absolute number of tumor buds per image with a very good correlation to the manually segmented ground truth (R2 value of 0.86).

Furthermore the automatic evaluation of whole-slide images from 20 CRC-patients, we found that neither the detected number of tumor buds at the invasion front nor the number in hotspots was associated with the nodal status. However, the number of spatial clusters of tumor buds (budding hotspots) significantly correlated to the nodal status (p-value = 0.003 for N0 vs. N1/N2). TMAs were not feasible for tumor budding evaluation, as the spatial relationship of tumor buds (especially hotspots) was not preserved.

Conclusions

Automatic image processing is a feasible and valid assessment tool for tumor budding in CRC on whole-slide images. Interestingly, only the spatial clustering of the tumor buds in hotspots (and especially the number of hotspots) and not the absolute number of tumor buds showed a clinically relevant correlation with patient outcome in our data.

Electronic supplementary material

The online version of this article (10.1186/s13000-018-0739-3) contains supplementary material, which is available to authorized users.

A predictive nomogram improved diagnostic accuracy and interobserver agreement of perirectal lymph nodes metastases in rectal cancer

Objective

To develop a predictive nomogram to improve the diagnostic accuracy and interobserver agreement of pre-therapeutic lymph nodes metastases in patients with rectal cancer.

Materials and Methods

An institutional database of 411 patients with rectal cancer was used to develop a nomogram to predict perirectal lymph nodes metastases. Patients' clinicopathological and MRI-assessed imaging variables were included in the multivariate logistic regression analysis. The model was externally validated and the performance was assessed by area under curve (AUC) of the receiver operator characteristics (ROC) curves. The interobserver agreement was measured between two independent radiologists.

Results

The diagnostic accuracy of the conventional MRI-assessed cN stage was 68%; 14.2% of the patients were over-staged and 17.8% of the patients were under-staged. A total of 35.1% of the patients had disagreed diagnosis for the cN stage between the two radiologists, with a kappa value of 0.295. A nomogram for predicting pathological lymph nodes metastases was successfully developed, with an AUC of 0.78 on the training data and 0.71 on the validation data. The predictors included in the nomogram were MRI cT stage, CRM involvement, preoperative CEA, tumor grade and lymph node size category. This nomogram yielded improved prediction in cN stage than the conventional MRI-based assessment.

Conclusions

By incorporating clinicopathological and MRI imaging features, we established a nomogram that improved the diagnostic accuracy and remarkably minimized the interobserver disagreement in predicting lymph nodes metastases in rectal cancers.

Predictive relevance of lymphovascular invasion in T1 colorectal cancer before endoscopic treatment

BACKGROUND AND AIM

 The depth of tumor invasion is currently the only reliable predictive risk factor for lymph node metastasis before endoscopic treatment for colorectal cancer. However, the most important factor to predict lymph node metastasis has been suggested to be lymphovascular invasion rather than the depth of invasion. Thus, the aim of this study was to investigate the predictive relevance of lymphovascular invasion before endoscopic treatment.

METHODS

 The data on pT1 colorectal cancers that were resected endoscopically or surgically from 2007 to 2015 were retrospectively reviewed. The cases were categorized into two groups: positive or negative for lymphovascular invasion. The following factors were evaluated by univariate and multivariate analyses: age and sex of the patients; location, size, and morphology of the lesion; and depth of invasion.

RESULTS

 The positive and negative groups included 229 and 457 cases, respectively. Younger age ( P  < 0.01), smaller lesion size ( P  = 0.01), non-LST (LST: laterally spreading tumor) ( P  < 0.01), presence of depression ( P  < 0.01), and pT1b ( P  < 0.01) were associated with lymphovascular invasion. In multivariate analysis, younger age (comparing patients aged ≤ 64 years with those aged > 65 years, OR, 1.81; 95 %CI, 1.29 - 2.53), presence of depression (OR, 1.97; CI, 1.40 - 2.77), non-LST features (OR, 1.50; CI, 1.04 - 2.15), and pT1b (OR, 3.08; CI, 1.91 - 4.97) were associated with lymphovascular invasion.

CONCLUSION

 Younger age, presence of depression, T1b, and non-LST are associated with lymphovascular invasion. Therefore, careful pathological diagnosis and surveillance are necessary for lesions demonstrating any of these four factors.

Successful identification of a predictive biomarker for lymph node metastasis in colorectal cancer using a proteomic approach

Colorectal cancer (CRC)-associated mortality is primarily caused by lymph node (LN) and distant metastasis, highlighting the need for biomarkers that predict LN metastasis and facilitate better therapeutic strategies. We used an Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-based comparative proteomics approach to identify novel biomarkers for predicting LN metastasis in CRC patients. We analyzed five paired samples of CRC with or without LN metastasis, adjacent normal mucosa, and normal colon mucosa, and differentially expressed proteins were identified and subsequently validated at the protein and/or mRNA levels by immunohistochemistry and qRT-PCR, respectively. We identified 55 proteins specifically associated with LN metastasis, from which we selected ezrin for further analysis and functional assessment. Expression of ezrin at both the protein and mRNA levels was significantly higher in CRC tissues than in adjacent normal colonic mucosa. In univariate analysis, high ezrin expression was significantly associated with tumor progression and poor prognosis, which was consistent with our in vitro findings that ezrin promotes the metastatic capacity of CRC cells by enabling cell invasion and migration. In multivariate analysis, high levels of ezrin protein and mRNA in CRC samples were independent predictors of LN metastasis. Our data thus identify ezrin as a novel protein and mRNA biomarker for predicting LN metastasis in CRC patients.

Recommendations for reporting tumor budding in colorectal cancer based on the International Tumor Budding Consensus Conference (ITBCC) 2016

Tumor budding is a well-established independent prognostic factor in colorectal cancer but a standardized method for its assessment has been lacking. The primary aim of the International Tumor Budding Consensus Conference (ITBCC) was to reach agreement on an international, evidence-based standardized scoring system for tumor budding in colorectal cancer. The ITBCC included nine sessions with presentations, a pre-meeting survey and an e-book covering the key publications on tumor budding in colorectal cancer. The 'Grading of Recommendation Assessment, Development and Evaluation' method was used to determine the strength of recommendations and quality of evidence. The following 10 statements achieved consensus: tumor budding is defined as a single tumor cell or a cell cluster consisting of four tumor cells or less (22/22, 100%). Tumor budding is an independent predictor of lymph node metastases in pT1 colorectal cancer (23/23, 100%). Tumor budding is an independent predictor of survival in stage II colorectal cancer (23/23, 100%). Tumor budding should be taken into account along with other clinicopathological features in a multidisciplinary setting (23/23, 100%). Tumor budding is counted on H&E (19/22, 86%). Intratumoral budding exists in colorectal cancer and has been shown to be related to lymph node metastasis (22/22, 100%). Tumor budding is assessed in one hotspot (in a field measuring 0.785 mm2) at the invasive front (22/22, 100%). A three-tier system should be used along with the budding count in order to facilitate risk stratification in colorectal cancer (23/23, 100%). Tumor budding and tumor grade are not the same (23/23, 100%). Tumor budding should be included in guidelines/protocols for colorectal cancer reporting (23/23, 100%). Members of the ITBCC were able to reach strong consensus on a single international, evidence-based method for tumor budding assessment and reporting. It is proposed that this method be incorporated into colorectal cancer guidelines/protocols and staging systems.

Proteomics analysis of differential protein expression identifies heat shock protein 47 as a predictive marker for lymph node metastasis in patients with colorectal cancer

The discovery of biomarkers to predict the potential for lymph node (LN) metastasis in patients with colorectal cancer (CRC) is essential for developing improved strategies for treating CRC. In the present study, they used isobaric tags for relative and absolute quantitation to conduct a proteomic analysis designed to identify novel biomarkers for predicting LN metastasis in patients with CRC. They identified 60 differentially expressed proteins specifically associated with LN metastasis in CRC patients and classified the molecular and functional characteristics of these proteins by bioinformatic approaches. A literature search led them to select heat shock protein 47 (HSP47) as the most suitable candidate biomarker for predicting LN metastasis. Validation analysis by immunohistochemistry showed that HSP47 expression in patients with CRC and the number of HSP47-positive spindle cells in the tumor stroma were significantly higher compared with those in adjacent normal colonic mucosa, and the number of the latter cells increased with tumor progression. Further, the number of HSP47-positive spindle cells in stroma was a more informative marker for identifying LN metastasis than HSP47expression. Multivariate analysis identified spindle cells that expressed elevated levels of HSP47 as an independent predictive biomarker for CRC with LN metastasis. Moreover, these cells served as an independent marker of disease-free and overall survival of patients with CRC. Their data indicate that the number of HSP47-positive spindle cells in the stroma of CRC may serve as a novel predictive biomarker of LN metastasis, early recurrence and poor prognosis.