Background: Conventional methods for predicting treatment response to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) are limited. Methods: This study retrospectively recruited 134 LARC patients who underwent standard nCRT followed by total mesorectal excision surgery in our institution. Based on pre-operative axial T2-weighted images, machine learning radiomics was performed. A receiver operating characteristic (ROC) curve was performed to test the efficiencies of the predictive model. Results: Among the 134 patients, 32 (23.9%) achieved pathological complete response (pCR), 69 (51.5%) achieved a good response, and 91 (67.9%) achieved down-staging. For prediction of pCR, good-response, and down-staging, the predictive model demonstrated high classification efficiencies, with an AUC value of 0.91 (95% CI: 0.83–0.98), 0.90 (95% CI: 0.83–0.97), and 0.93 (95% CI: 0.87–0.98), respectively. Conclusion: Our machine learning radiomics model showed promise for predicting response to nCRT in patients with LARC. Our predictive model based on the commonly used T2-weighted images on pelvic Magnetic Resonance Imaging (MRI) scans has the potential to be adapted in clinical practice. Novelty and Impact Statements: Methods for predicting the response of the locally advanced rectal cancer (LARC, T3-4, or N+) to neoadjuvant chemoradiotherapy (nCRT) is lacking. In the present study, we developed a new machine learning radiomics method based on T2-weighted images. As a non-invasive tool, this method facilitates prediction performance effectively. It achieves a satisfactory overall diagnostic accuracy for predicting of pCR, good response, and down-staging show an AUC of 0.908, 0.902, and 0.930 in LARC patients, respectively.

Intrinsic and acquired resistance to targeted therapies is a significant clinical problem in cancer. We previously showed that resistance to regorafenib, a multi-kinase inhibitor for treating colorectal cancer (CRC) patients, can be caused by mutations in the tumor suppressor FBW7 , which block degradation of the pro-survival Bcl-2 family protein Mcl-1. We tested if Mcl-1 inhibition can be used to develop a precision combination therapy for overcoming regorafenib resistance. Methods: Small-molecule Mcl-1 inhibitors were tested on CRC cells with knock-in (KI) of a non-degradable Mcl-1. Effects of Mcl-1 inhibitors on regorafenib sensitivity were determined in FBW7 -mutant and -wild-type (WT) CRC cells and tumors, and in those with acquired regorafenib resistance due to enriched FBW7 mutations. Furthermore, translational potential was explored by establishing and analyzing FBW7 -mutant and -WT patient-derived organoid (PDO) and xenograft (PDX) tumor models. Results: We found that highly potent and specific Mcl-1 inhibitors such as S63845 overcame regorafenib resistance by restoring apoptosis in multiple regorafenib-resistant CRC models. Mcl-1 inhibition re-sensitized CRC tumors with intrinsic and acquired regorafenib resistance in vitro and in vivo, including those with FBW7 mutations. Importantly, Mcl-1 inhibition also sensitized FBW7 -mutant PDO and PDX models to regorafenib. In contrast, Mcl-1 inhibition had no effect in FBW7 -WT CRCs. Conclusions: Our results demonstrate that Mcl-1 inhibitors can overcome intrinsic and acquired regorafenib resistance in CRCs by restoring apoptotic response. FBW7 mutations might be a potential biomarker predicting for response to the regorafenib/Mcl-1 inhibitor combination.

Previous studies demonstrated that several inflammation-based hematological indices are closely related to various malignancies, including colorectal cancer (CRC). In this study, the prognostic value of inflammation-based markers, including a combination index termed coNLR-PDW, comprising the preoperative neutrophil-to-lymphocyte ratio (NLR) and the platelet distribution width (PDW), was evaluated in 206 patients with non-metastatic CRC treated with surgery at a single medical center. The association of patient demographics, blood chemistry, and serum biochemical indices with recurrence-free survival (RFS) and overall survival (OS) were examined through univariate and multivariate analysis. Receiver operating characteristic curve analysis revealed the optimal cut-off values of the NLR and lymphocyte-to-monocyte ratio (LMR) to be, respectively, 2.0 and 3.32 for both RFS and OS. For PDW, cut-off values of 17.25% and 17.35% were defined for RFS and OS, respectively. On univariate analysis, lymph node involvement, stage, presence of intravascular emboli (IVE), carbohydrate antigen 199 (CA199) ≥ 35 kU/L, NLR ≥ 2.0, LMR ≤ 3.32, elevated PDW, a high coNLR-PDW score, high blood glucose, and high neutrophil and lymphocyte percentages correlated with poorer RFS and OS (P < 0.05). On multivariate analysis, lymph node involvement, IVE, CA199, PDW, and coNLR-PDW correlated with both RFS and OS (P < 0.05), while NLR correlated only with OS (P = 0.001). These results highlight the usefulness of the coNLR-PDW index as a prognostic marker of non-metastatic CRC outcome. In clinical practice, its assessment could contribute to establishing more personalized regimes for patients undergoing tumor resection surgery.

Background and Aims: The aim of this study was to analyse the landscape of publications on rectal cancer (RC) over the past 25 years by machine learning and semantic analysis. Methods: Publications indexed in PubMed under the Medical Subject Headings (MeSH) term ‘Rectal Neoplasms’ from 1994 to 2018 were downloaded in September 2019. R and Python were used to extract publication date, MeSH terms and abstract from the metadata of each publication for bibliometric assessment. Latent Dirichlet allocation was applied to analyse the text from the articles’ abstracts to identify more specific research topics. Louvain algorithm was used to establish a topic network resulting in identifying the relationship between the topics. Results: A total of 23,492 papers published were identified and analysed in this study. The changes of research focus were analysed by the changing of MeSH terms. Studied contents extracted from the publications were divided into five areas, including surgical intervention, radiotherapy and chemotherapy intervention, clinical case management, epidemiology and cancer risk as well as prognosis studies. Conclusions: The number of publications indexed on RC has expanded rapidly over the past 25 years. Studies on RC have mainly focused on five areas. However, studies on basic research, postoperative quality of life and cost-effective research were relatively lacking. It is predicted that basic research, inflammation and some other research fields might become the potential hotspots in the future.

Background: There is no conclusion about the most important contributor to the upswing of locally advanced colorectal cancer (LACRC) survival. Methods: Data from the Surveillance, Epidemiology, and End Results (SEER) database was extracted to identify colorectal adenocarcinoma cancer patients at stage II and III diagnosed in the two periods 1989–1990 and 2009–2010. The statistical methods included Pearson’s chi-squared test, log-rank test, Cox regression model and propensity score matching. Results: The Cox regression model showed that hazard ratio (HR) of non-surgery dropped from 11.529 to 3.469 in right colon cancer (RCC), 5.214 to 2.652 in left colon cancer (LCC) and 3.275 to 3.269 in rectal cancer (RC) from 1989–1990 to 2009–2010. The 95% confidence intervals (CIs) for surgical resection in 2009–2010 were narrower than those in 1989–1990. HR became greater in LACRC without chemotherapy (from 1.337 to 1.779 in RCC, 1.269 to 2.017 in LCC, 1.317 to 1.811 in RC). There was no overlapping about the 95% CI of chemotherapy between the two groups. The progress of surgery was not linked to the improvement of overall survival (OS) of RCC ( p = 0.303) and RC ( p = 0.660). Chemotherapy had a significant association with OS of all colorectal cancer (CRC) patients ( p = 0.017 in RCC; p = 0.006 in LCC; p = 0.001 in RC). Conclusions: Advancements in chemotherapy regimen were the main contributor to the upswing of CRC survival. The improvements in surgery had a limited effect on improvements in CRC survival.