What We Know About Stage II and III Colon Cancer: It's Still Not Enough.
ABSTRACT: The introduction of oxaliplatin as adjuvant treatment for stage III colon cancer in 2004 has been the last practice changing progress in adjuvant treatment for patients with early colon cancer. Since then, many prognostic and predictive biomarkers have been studied, but only DNA mismatch repair status has been validated as having an important prognostic value. Accordingly, TNM and clinical-pathological patterns, such as pT4 lesions and lymph node sampling <12 nodes, are the main factors that guide physicians' choice regarding adjuvant treatment. More recently, many biomarkers showed promising results: POLE, ErbB2, CDX2, SMAD4, BRAF and KRAS. In addition to these, immune-contexture, molecular classification, and gene signatures could become new ways to better classify colon cancer patients with more discriminatory power than TNM. The aim of this review is to report the state-of-the-art of prognostic and predictive factors in the adjuvant setting and which of these could modify clinical practice and maybe replace TNM classification.
Project description:The current pT3N0 category represents a heterogeneous subgroup involving tumor size, separate tumor nodes in one lobe, and locoregional growth pattern. We aim to validate outcomes according to the eighth edition of the TNM staging classification. A total of 281 patients who had undergone curative lung cancer surgery staged with TNM-7 in two German centers were retrospectively analyzed. The subtypes tumor size >7 cm and multiple nodules were grouped as T3a, and the subtypes parietal pleura invasion and mixed were grouped as T3b. We stratified survival by subtype and investigated the relative benefit of adjuvant chemotherapy according to subtype. The 5-year overall survival (OS) rates differed between the different subtypes tumor diameter >7 cm (71.5%), multiple nodules in one lobe (71.0%) (grouped as T3a), parietal pleura invasion (59.%), and mixed subtype (5-year OS 50.3%) (grouped as T3b), respectively. The cohort as a whole did not gain significant OS benefit from adjuvant chemotherapy. In contrast, adjuvant chemotherapy significantly improved OS in the T3b subgroup (logrank <i>p</i> = 0.03). This multicenter cohort analysis of pT3N0 patients identifies a new prognostic mixed subtype. Tumors >7 cm should not be moved to pT4. Patients with T3b tumors have significantly worse survival than patients with T3a tumors.
Project description:Background: The current model for predicting prognosis and chemotherapy response of patients with gastric adenocarcinoma is the TNM staging system, which may lack adequate accuracy and evaluations of molecular features at the individual level. We aimed to develop a prediction model to assess the individualized prognosis and responsiveness to fluorouracil-based adjuvant chemotherapy. Method: This retrospective study concluded 2 independent cohorts of patients with GAC. The expression of dysbindin was quantified and evaluated the association with the overall survival for GAC patients. A prediction model for postoperative overall survival was generated and internally and externally validated. The interaction between dysbindin expression and PACT was detected in advanced GAC patients. Results: Of the 637 patients enrolled in the study, 425 were men (66.7%) with a mean (SD) age of 59.79 (9.81) years. High levels of dysbindin expression predicted a poor prognosis in patients with GAC. Multivariate analysis demonstrated dysbindin expression was an independent prognostic predictor of overall survival in the test, validation and combined cohorts. A prognostic predictive model incorporating age, dysbindin expression, pathological differentiation, Lauren's classification and the TNM staging system was established. This model had better predictive accuracy for overall survival than the traditional TNM staging system and was internally and externally validated. More importantly, advanced GAC patients with low dysbindin expression were likely to benefit from fluorouracil-based PACT. Conclusion: The risk stratification model incorporating dysbindin expression and TNM staging system showed better predictive accuracy. Advanced GAC patients with low dysbindin expression revealed better response of fluorouracil-based adjuvant chemotherapy.
Project description:(1) Background: The aim of this study was to develop a prediction model for assessing individual mPC risk in patients with pT4 colon cancer. Methods: A total of 2003 patients with pT4 colon cancer undergoing R0 resection were categorized into the training or testing set. Based on the training set, 2044 Cox prediction models were developed. Next, models with the maximal C-index and minimal prediction error were selected. The final model was then validated based on the testing set using a time-dependent area under the curve and Brier score, and a scoring system was developed. Patients were stratified into the high- or low-risk group by their risk score, with the cut-off points determined by a classification and regression tree (CART). (2) Results: The five candidate predictors were tumor location, preoperative carcinoembryonic antigen value, histologic type, T stage and nodal stage. Based on the CART, patients were categorized into the low-risk or high-risk groups. The model has high predictive accuracy (prediction error ≤5%) and good discrimination ability (area under the curve >0.7). (3) Conclusions: The prediction model quantifies individual risk and is feasible for selecting patients with pT4 colon cancer who are at high risk of developing mPC.
Project description:Background: The present study analyzed the nonbiological factors (NBFs) together with the American Joint Committee on Cancer (AJCC) Tumor-Node-Metastasis (TNM) staging system to generate a refined, risk-adapted stage for the clinical treatment of colon cancer. Methods: Eligible patients (N = 28,818) with colon cancer between 1 January 2010 and 31 December 2014, were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier curves and Cox proportional hazards regression, analyzed the probabilities of cancer-specific survival (CSS) in patients with colon cancer, with different NBF-TNM stages. Results: Insurance status, marital status, and median household income were significant prognostic NBFs in the current study (p < 0.05). The concordance index of NBF-TNM stage was 0.857 (95% confidence interval (CI) = 0.8472?0.8668). Multivariate Cox analyses, indicated that NBF1-stage was independently associated with a 50.4% increased risk of cancer-specific mortality in colon cancer (p < 0.001), which increased to 77.1% in non-metastatic colon cancer. NBF0-stage improved in CSS as compared to the NBF1-stage in the respective stages (p < 0.05). Conclusions: The new proposed NBF-stage was an independent prognostic factor in colon cancer. Effect of NBFs on the survival of colon cancer necessitates further clinical attention. Moreover, the incorporation of NBF-stage into the AJCC TNM staging system is essential for prognostic prediction, and clinical guidance of adjuvant chemotherapy in stage II and III colon cancer.
Project description:About 20 percent of TNM-stage II colon cancer patients who are treated by surgical resection develop recurrence, and adjuvant chemotherapy in this group is still debated among researchers and clinicians. Currently, adverse histopathological and clinical factors are used to select patients for adjuvant chemotherapy following surgery. However, additional biomarkers to classify patients at risk of recurrence are needed. We have conducted a study using fresh frozen tumor tissue from 54 TNM-stage II colon cancer patients and performed microRNA profiling using next-generation sequencing. For the selection of the prognostic microRNAs, a LASSO Cox Regression model was employed. For the validation, we used the publically available TCGA-COAD cohort (n?=?122). A prognostic panel of four micorRNAs (hsa-miR-5010-3p, hsa-miR-5100, hsa-miR-656-3p and hsa-miR-671-3p) was identified in the study cohort and validated in the TCGA-COAD cohort. The four-microRNA classifier successfully identified high-risk patients in the study cohort (P?<?0.001) and the validation cohort (P?=?0.005). Additionally, a number of established risk factors and the four-miRNA classifier were used to construct a nomogram to evaluate risk of recurrence. We identified a four-microRNA classifier in patients with TNM-stage II colon cancer that can be used to discriminate between patients at low- and high risk of recurrence.
Project description:The consensus Immunoscore is a routine assay quantifying the adaptive immune response within the tumor microenvironment. It has a prognostic value that has been confirmed in a phase 3 clinical trial (NCCTG N0147) in stage III colon cancers. Moreover, results from another phase 3 randomized trial revealed the predictive value of Immunoscore for response to adjuvant chemotherapy duration. These results highlight the clinical utility of Immunoscore. In its latest edition, the World Health Organization classification of Digestive System Tumors introduced for the first time the immune response as an essential and desirable diagnostic criterion for colorectal cancer. Within the tumor microenvironment, the immune response provides an important estimate of the risk of recurrence and death in colon cancer. The international validation of the prognostic value of the consensus Immunoscore together with its prognostic value in the N0147 trial and its predictive utility for response to chemotherapy in stage III patients provide valuable information for patient management.
Project description:<h4>Background</h4>We aimed to evaluate the cost-effectiveness of risk-based strategies to improve the selection of surgically treated stage II colon cancer (CC) patients for adjuvant chemotherapy.<h4>Methods</h4>Using the 'Personalized Adjuvant TreaTment in EaRly stage coloN cancer' (PATTERN) model, we evaluated five selection strategies: (1) no chemotherapy, (2) Dutch guideline recommendations assuming observed adherence, (3) Dutch guideline recommendations assuming perfect adherence, (4) biomarker mutation OR pT4 stage strategy in which patients with <i>MSS</i> status combined with a pT4 stage or a mutation in <i>BRAF</i> and/or <i>KRAS</i> receive chemotherapy assuming perfect adherence and (5) biomarker mutation AND pT4 stage strategy in which patients with <i>MSS</i> status combined with a pT4 stage tumor and a <i>BRAF</i> and/or <i>KRAS</i> mutation receive chemotherapy assuming perfect adherence. Outcomes were number of CC deaths per 1000 patients and total discounted costs and quality-adjusted life-years (QALYs) per patient (pp). Analyses were conducted from a societal perspective. The robustness of model predictions was assessed in sensitivity analyses.<h4>Results</h4>The reference strategy, that is, no adjuvant chemotherapy, resulted in 139 CC deaths in a cohort of 1000 patients, 8.077 QALYs pp and total costs of €22,032 pp. Strategies 2-5 were more effective (range 8.094-8.217 QALYs pp and range 118-136 CC deaths per 1000 patients) and more costly (range €22,404-€25,102 pp). Given a threshold of €50,000/QALY, the optimal use of resources would be to treat patients with either the full adherence strategy and biomarker mutation OR pT4 stage strategy.<h4>Conclusion</h4>Selection of stage II CC patients for chemotherapy can be improved by either including biomarker status in the selection strategy or by improving adherence to the Dutch guideline recommendations.
Project description:<h4>Background</h4>The aim of this study was to investigate the value of the cyclin D1 isoforms D1a and D1b as prognostic factors and their relevance as predictors of response to adjuvant chemotherapy with 5-fluorouracil and levamisole (5-FU/LEV) in colorectal cancer (CRC).<h4>Methods</h4>Protein expression of nuclear cyclin D1a and D1b was assessed by immunohistochemistry in 335 CRC patients treated with surgery alone or with adjuvant therapy using 5-FU/LEV. The prognostic and predictive value of these two molecular markers and clinicopathological factors were evaluated statistically in univariate and multivariate survival analyses.<h4>Results</h4>Neither cyclin D1a nor D1b showed any prognostic value in CRC or colon cancer patients. However, high cyclin D1a predicted benefit from adjuvant therapy measured in 5-year relapse-free survival (RFS) and CRC-specific survival (CSS) compared to surgery alone in colon cancer (P=0.012 and P=0.038, respectively) and especially in colon cancer stage III patients (P=0.005 and P=0.019, respectively) in univariate analyses. An interaction between treatment group and cyclin D1a could be shown for RFS (P=0.004) and CSS (P=0.025) in multivariate analysis.<h4>Conclusion</h4>Our study identifies high cyclin D1a protein expression as a positive predictive factor for the benefit of adjuvant 5-FU/LEV treatment in colon cancer, particularly in stage III colon cancer.
Project description:Background:TNM staging alone does not accurately predict outcome in colon cancer (CC) patients who may be eligible for adjuvant chemotherapy. It is unknown to what extent the molecular markers microsatellite instability (MSI) and mutations in BRAF or KRAS improve prognostic estimation in multivariable models that include detailed clinicopathological annotation. Patients and methods:After imputation of missing at random data, a subset of patients accrued in phase 3 trials with adjuvant chemotherapy (n?=?3016)-N0147 (NCT00079274) and PETACC3 (NCT00026273)-was aggregated to construct multivariable Cox models for 5-year overall survival that were subsequently validated internally in the remaining clinical trial samples (n?=?1499), and also externally in different population cohorts of chemotherapy-treated (n?=?949) or -untreated (n?=?1080) CC patients, and an additional series without treatment annotation (n?=?782). Results:TNM staging, MSI and BRAFV600E mutation status remained independent prognostic factors in multivariable models across clinical trials cohorts and observational studies. Concordance indices increased from 0.61-0.68 in the TNM alone model to 0.63-0.71 in models with added molecular markers, 0.65-0.73 with clinicopathological features and 0.66-0.74 with all covariates. In validation cohorts with complete annotation, the integrated time-dependent AUC rose from 0.64 for the TNM alone model to 0.67 for models that included clinicopathological features, with or without molecular markers. In patient cohorts that received adjuvant chemotherapy, the relative proportion of variance explained (R2) by TNM, clinicopathological features and molecular markers was on an average 65%, 25% and 10%, respectively. Conclusions:Incorporation of MSI, BRAFV600E and KRAS mutation status to overall survival models with TNM staging improves the ability to precisely prognosticate in stage II and III CC patients, but only modestly increases prediction accuracy in multivariable models that include clinicopathological features, particularly in chemotherapy-treated patients.
Project description:The interaction of glycoprotein 130 (gp130) with the cytokines of Interleukin-6 (IL-6) family has proved to play a crucial part in several cancers. Our current study is designed to discover the clinical prognostic significance of gp130 in non-metastatic gastric cancer. We examined intratumoral gp130 expression in retrospectively enrolled 370 gastric cancer patients who underwent radical gastrectomy with standard D2 lymphadenectomy at Zhongshan Hospital of Fudan University during 2007 and 2008 by immunohistochemical staining. The expression of gp130 was significantly correlated with T classification, N classification and TNM stage (P?=?0.003, P?<?0.001 and P?<?0.001, respectively; T, N, TNM refers to Tumor Invasion, Regional lymph node metastasis and Tumor Node Metastasis, respectively). Elevated intratumoral gp130 expression implied unfavourable overall survival (OS) (P?<?0.001) and disease-free survival (DFS) (P?<?0.001), respectively. Furthermore, among TNM II and III gp130-high patients, those who were treated with 5-fluorouracil (5-FU) based adjuvant chemotherapy had better OS (P?<?0.001). The generated nomogram performed well in predicting the 3- and 5-year OS of gastric cancer patients. The incorporation of gp130 into contemporary TNM staging system would be of great significance to improve the current individual risk stratification. These findings contribute to better clinical management for those patients who would benefit from adjuvant chemotherapy.