What is the optimal means of staging colon cancer?

Molecular Mechanisms of Dietary Compounds in Cancer Stem Cells from Solid Tumors: Insights into Colorectal, Breast, and Prostate Cancer

Cancer stem cells (CSC) are known to be the main source of tumor relapse, metastasis, or multidrug resistance and the mechanisms to counteract or eradicate them and their activity remain elusive. There are different hypotheses that claim that the origin of CSC might be in regular stem cells (SC) and, due to accumulation of mutations, these normal cells become malignant, or the source of CSC might be in any malignant cell that, under certain environmental circumstances, acquires all the qualities to become CSC. Multiple studies indicate that lifestyle and diet might represent a source of wellbeing that can prevent and ameliorate the malignant phenotype of CSC. In this review, after a brief introduction to SC and CSC, we analyze the effects of phenolic and non-phenolic dietary compounds and we highlight the molecular mechanisms that are shown to link diets to CSC activation in colon, breast, and prostate cancer. We focus the analysis on specific markers such as sphere formation, CD surface markers, epithelial-mesenchymal transition (EMT), Oct4, Nanog, Sox2, and aldehyde dehydrogenase 1 (ALDH1) and on the major signaling pathways such as PI3K/Akt/mTOR, NF-κB, Notch, Hedgehog, and Wnt/β-catenin in CSC. In conclusion, a better understanding of how bioactive compounds in our diets influence the dynamics of CSC can raise valuable awareness towards reducing cancer risk.

The impact of tumor size on the prognosis and chemotherapy efficacy in stage I/II colon cancer patients

Background: The impact of tumor size on the survival and chemotherapy reponse of early-stage colon cancer remains unclear. Our study explored the effect of tumor size on overall survival (OS) and postoperative chemotherapy efficacy in patients with stage I/II colon cancer. Methods: Stage I/II colon cancer patients from the Surveillance, Epidemiology and End Results (SEER) database and a China center were extracted as two cohorts respectively. X-tile program was adopted to acquire optimal cutoff points of tumor size (16mm and 49mm). Harrell's concordance index (c-index) and time-dependent receiver operating characteristic curve (ROC) were used to indicate discrimination ability of prognostic factors. Results: Overall, 104,908 and 168 stage I/II postoperative colon cancer patients from SEER database and a China center were eligible, respectively. Kaplan-Meier analysis showed that large tumor size was associated with poor OS in two cohorts. The effect of tumor size on OS gradually decreased as the T stage increased both before PSM (c-index 0.535 for T1N0M0 and 0.506 for T4N0M0, p<0.05) and after PSM (c-index 0.543 for T1N0M0, p<0.05; c-index 0.543 for T4N0M0, p>0.05). Stratified analyses showed that chemotherapy improved the OS rate by 9.5% (chemotherapy vs. non-chemotherapy: 83.5% vs. 73.0%) or 12.8% (chemotherapy vs. non-chemotherapy: 85.7% vs. 72.9%) before and after PSM in T2N0M0 patients with tumor size >49 mm, but not in T1N0M0. The survival benefit provided by chemotherapy for T2N0M0 patients with large tumor was also validated in the Chinese cohort. Conclusions: Large tumor size was a risk factor for stage I/II colon cancer, especially for T1N0M0. Tumor size could serve as a complementary factor guiding postoperative chemotherapy for T2N0M0 patients.

Deep Learning with Multimodal Integration for Predicting Recurrence in Patients with Non-Small Cell Lung Cancer

Due to high recurrence rates in patients with non-small cell lung cancer (NSCLC), medical professionals need extremely accurate diagnostic methods to prevent bleak prognoses. However, even the most commonly used diagnostic method, the TNM staging system, which describes the tumor-size, nodal-involvement, and presence of metastasis, is often inaccurate in predicting NSCLC recurrence. These limitations make it difficult for clinicians to tailor treatments to individual patients. Here, we propose a novel approach, which applies deep learning to an ensemble-based method that exploits patient-derived, multi-modal data. This will aid clinicians in successfully identifying patients at high risk of recurrence and improve treatment planning.

SLC6A14, a Na+/Cl--coupled amino acid transporter, functions as a tumor promoter in colon and is a target for Wnt signaling

SLC6A14 is a Na⁺/Cl⁻-coupled transporter for neutral and cationic amino acids. It is expressed at basal levels in the normal colon but is up-regulated in colon cancer. However, the relevance of this up-regulation to cancer progression and the mechanisms involved in the up-regulation remain unknown. Here, we show that SLC6A14 is essential for colon cancer and that its up-regulation involves, at least partly, Wnt signaling. The up-regulation of the transporter is evident in most human colon cancer cell lines and also in a majority of patient-derived xenografts. These findings are supported by publicly available TCGA (The Cancer Genome Atlas) database. Treatment of colon cancer cells with α-methyltryptophan (α-MT), a blocker of SLC6A14, induces amino acid deprivation, decreases mTOR activity, increases autophagy, promotes apoptosis, and suppresses cell proliferation and invasion. In xenograft and syngeneic mouse tumor models, silencing of SLC6A14 by shRNA or blocking its function by α-MT reduces tumor growth. Similarly, the deletion of Slc6a14 in mice protects against colon cancer in two different experimental models (inflammation-associated colon cancer and genetically driven colon cancer). In colon cancer cells, expression of the transporter is reduced by Wnt antagonist or by silencing of β-catenin whereas Wnt agonist or overexpression of β-catenin shows the opposite effect. Finally, SLC6A14 as a target for β-catenin is confirmed by chromatin immunoprecipitation. These studies demonstrate that SLC6A14 plays a critical role in the promotion of colon cancer and that its up-regulation in cancer involves Wnt signaling. These findings identify SLC6A14 as a promising drug target for the treatment of colon cancer.

Real-World Implications of Nonbiological Factors with Staging, Prognosis and Clinical Management in Colon Cancer

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.

Real-world study of a novel prognostic scoring system: for a more precise prognostication and better clinical treatment guidance in stages II and III colon cancer

PURPOSE

This study aimed to improve the American Joint Committee on Cancer (AJCC) Tumor Node Metastases (TNM) staging system and demonstrate the improvement in prognostic accuracy and clinical management guidance in colon cancer using the novel prognostic score (P score).

METHODS

Eligible patients were identified using the Surveillance, Epidemiology, and End Results database. A P score (based on age, tumor size, and tumor grade) was assigned to each patient. The Cox proportional hazards regression analyses were performed to identify independent factors associated with prognosis. The Kaplan-Meier survival curves were used to analyze the prognosis of patients with colon cancer with different P scores. The TNM staging system was compared with the P score in stages I-IV by calculating the concordance index.

RESULTS

The multivariate Cox analysis indicated that a higher P score was independently associated with a higher risk of cancer-specific mortality. The Kaplan-Meier survival curves showed that the survival benefit gradually increased as the P score decreased. The concordance index rose from 0.5, 0.593, 0.633, and 0.551 of AJCC TNM staging system to 0.709, 0.651, 0.691, and 0.623 of P score in stages I-IV, respectively.

CONCLUSIONS

The P score was an independent prognostic factor of colon cancer and had a much better prognostic accuracy than the AJCC TNM staging system in all patients with colon cancer. It may help in identifying patients with high-risk stage II colon cancer who were candidates for adjuvant therapy and differentiating patients with stage III colon cancer for adjuvant therapy.

P-TNM staging system for colon cancer: combination of P-stage and AJCC TNM staging system for improving prognostic prediction and clinical management

Aim

This study focused on improving the American Joint Committee on Cancer TNM staging system and demonstrated an improvement in prognostic accuracy and clinical management of colon cancer using the P-TNM staging system.

Patients and methods

Eligible patients (N=56,800) were identified from the Surveillance, Epidemiology, and End Results database between January 1, 2010, and December 31, 2014. The P-stage (P0 or P1) was assigned to each patient based on age at diagnosis, tumor grade, and tumor size. The outcome of interest was cancer-specific survival (CSS). The Cox proportional hazards regression analyses were used to identify independent prognostic factors and analyze the CSS probabilities of patients with colon cancer having different P-TNM stages, respectively.

Results

A total of 29,627 patients were assigned to P0-stage and 27,173 patients were assigned to P1-stage. The P1-stage was associated with a 98.1% increased risk of cancer-specific mortality (hazard ratio =1.981, 95% confidence interval =1.891-2.076, P<0.001), which was higher in patients with nonmetastatic colon cancer. The P1-stage patients had improvement in CSS compared with those in P0-stage in respective stages (P<0.001). Moreover, CSS decreased in stage I-P1 compared with stage IIA-P0 or IIIA-P0 (P<0.001), stage IIIA-P1 compared with stage IIA-P0 (P<0.001), stage IIB-P1 compared with stage IIIB-P0 or IIC-P0 (P<0.001), stage IIIB-P1 compared with stage IIC-P0 (P<0.001), and stage IIC-P1 compared with stage IIIC-P0 (P<0.001).

Conclusion

P-stage was an independent prognostic factor for colon cancer. This study strongly supported the incorporation of P-stage into the American Joint Committee on Cancer TNM staging system for a better approach to prognostication and, thus, more individualized risk-adaptive therapies in colon cancer.