Survival Of Colon Cancer Patients Research Articles

Enhanced patient journey associated with improved overall survival in colon cancer patients: A study by the Ligurian Oncology Network.

Colon cancer imposes a significant burden on global healthcare systems, necessitating efforts to improve oncology care quality and patient outcomes. We studied the correlation between care quality and survival outcomes among colon cancer patients within the Ligurian Oncology Network (Italy). We developed an Overall Quality Score (OQS) to evaluate the impact of oncology care quality on survival outcomes within the Ligurian Oncology Network. OQS indicators were selected through expert consensus, covering screening, diagnosis, treatment, and follow-up. A sample of colon cancer patients diagnosed in 2012 was randomly selected from administrative healthcare data. Analyses were performed using two models: a binary model (High and Low OQS) and a stratified model (Low, Medium, and High OQS). Statistical analysis involved survival curves, log-rank tests, and Cox proportional hazards models using SAS 9.4. Of 175 eligible colon cancer patients, 150 were included. Following a median follow-up of 7.6 years, a correlation between High-OQS (⩾ 65%) and prolonged disease-free survival was observed (unadjusted HR 0.57, 95%CI 0.33-0.99, log-rank p=0.041). The five-year disease-free survival rate for High-OQS patients was 70% (95%CI 57-80%), compared to 53% (95%CI 41-64%) for Low-OQS patients. Similarly, the five-year overall survival rate was 78% (95%CI 65-86%) for High-OQS patients, compared to 58% (95%CI 45-68%) for Low-OQS patients (unadjusted HR 0.56, 95%CI 0.31-1.00, log-rank p=0.048). Our findings highlight the potential impact of the patient journey on colon cancer survival outcomes. Optimising care pathways might improve patient outcomes in colon cancer management.

Cystathionine-β-synthase expression correlates with tumour progression and adverse prognosis in patients with colon cancer.

To investigate the levels of cystathionine-β-synthase (CBS) in colon cancer tissues compared with adjacent control tissues; and to examine the relationship between CBS level and clinical characteristics and prognosis. This retrospective study enrolled patients with primary colon cancer. Paraffin-embedded specimens were used to create pathological tissue microarrays. Immunohistochemistry was performed on the microarray to detect the levels of CBS in colon cancer tissues and normal adjacent tissues. Analyses were undertaken to examine the relationship between the level of CBS and clinical characteristics and prognosis. A total of 216 patients (107 males and 109 females) were included in the study. The level of CBS in cancer tissues was found to be significantly increased compared with normal adjacent control tissues. There were significant differences in tumour location, tumour-node-metastasis stage and survival rate between the CBS-negative and CBS-positive groups. Positive CBS immunostaining was associated with decreased survival in colon cancer patients. The results of multivariate Cox regression analysis revealed that tumour location and positive CBS immunostaining were independent prognostic factors for survival. Positive CBS immunostaining was closely associated with colon cancer and high levels of CBS might accelerate tumour development and affect patient prognosis in colon cancer.

Serum 25-Hydroxyvitamin D and Five-Year Survival in Primary Colon Cancer: A Retrospective Cohort Study

This study examined the link between serum 25-hydroxyvitamin D (25(OH)D) and mortality in patients with colon cancer. Using a clinical database from the University of California, serum 25(OH)D measures were averaged for the time following diagnosis until either the time of death or 5 years had elapsed. Analytical methods included the use of Generalized Additive Models (GAM), logistic regression, and Cox proportional hazards models to examine non-linear relationships and the impact of 25(OH)D on 5-year mortality. This study assessed 1,602 patients with colon cancer having a median 25(OH)D of 31.8 ng/mL and a 5-year mortality rate of 22.7%. A significant association between higher post-diagnosis vitamin D levels and decreased 5-year mortality was observed. This association persisted after adjusting for disease severity and significant demographic confounders, in both a logistic regression model for 5-year mortality (OR = 0.79, 95% CI: 0.66–0.92, p < 0.001) and a cox proportional hazards model for survival (HR = 0.94, CI: 0.88–0.99, p = 0.048). GAM illustrated a steep increase in survival probability up to a plateau, suggesting a threshold effect beyond roughly 50.0 ng/mL. This study found a potential protective role of vitamin D in the survival of colon cancer patients, supporting the correction of levels below 25 ng/mL but ideally above 50 ng/mL.

Intervention of epithelial mesenchymal transition against colon cancer cell growth and metastasis based on SOX21/POU4F2/Hedgehog signaling axis

AimsColon cancer poses a major threat to human health and a heavy burden on the national economy. As a member of the SOX transcription factor family, SRY-box transcription factor 21 (SOX21) is associated with various cancers, but its mechanism of action in colon cancer remains unclear. This study focused on the molecular mechanisms of transcription factor SOX21 in proliferation and metastasis of colon cancer cells. Main methodsWe analyzed SOX21 expression level and its impact on survival in colon cancer patients by bioinformatics analysis. We used public databases for gene correlation, GSEA enrichment analysis. Cell function experiments (colony formation assay, wound healing assay, Transwell migration and invasion assay) were utilized to determine the impact of SOX21 silencing and over-expression on cell proliferation and metastasis. The luciferase reporter assay, CUT&RUN-qPCR assay and Methylation Specific PCR were used to explore SOX21-POU class 4 homeobox 2 (POU4F2) molecular interactions. The molecular mechanisms were verified by Quantitative real-time PCR and Western blot analysis. Key findingsSOX21 is highly expressed and affects the overall survival of colon cancer patients. SOX21 can attenuates POU4F2 methylation state by binding with it. In addition, this interaction facilitate its transcriptional activation of Hedgehog pathway, mediates epithelial-mesenchymal transition (EMT), consequently promoting the proliferation and metastasis of colon cancer cells. SignificanceOur study reveals that SOX21 is an oncogenic molecule and suggests its regulatory role in colon carcinogenesis and progression, providing new insights into the treatment of this disease.

Evaluating Surgical Outcomes and Survival in Colon Cancer Patients Over 80 Years Old.

In the context of an increasing older population, knowing the surgical outcomes of older patients is of paramount importance to define a comprehensive strategy for colon cancer treatment in these patients. This study aimed to analyze the surgical outcomes and survival of patients over 80 years old undergoing surgery for colon cancer. This is an observational retrospective longitudinal study of patients over 80 years old with colon cancer diagnosis who underwent surgery for this condition, between 2018 and 2021, in a Portuguese hospital. Demographic and clinical features were characterized. Kaplan-Meier method was used for survival analysis. Out of 90 patients in the study, 41.1% were female. The majority (56.7%) had an Eastern Cooperative Oncology Group (ECOG) performance status of 1 or 0, with a median Charlson Comorbidity Index of 7.0. Tumors were primarily located in the right colon (52.2%) and sigmoid colon (25.6%), with most patients having stage II (35.6%) or stage III (25.5%) disease. Elective surgeries accounted for 73% of procedures, and 80.0% had curative intent, with laparoscopic surgery performed in 66.7% of cases. Only 8.3% of those undergoing curative-intent procedures received adjuvant chemotherapy. Emergent admissions were associated with more advanced cancer stages, higher rates of palliative intent procedures (45.8% versus 10.6%, p < 0.001), and more open surgeries (75.0% versus9.1%, p < 0.001) when compared to elective procedures. Postoperative mortality was higher in the emergent group (20.8% versus10.6%), though there was no association between the type of admission and postoperative complications. Median overall survival for all patients was 36.7 (95% CI 28.1 to 45.3) months, with significant differences between curative-intent and palliative surgeries (median of 39.8 (95% CI 32.6 to 47.0) versus 10.6 (95% CI 0.67 to 20.5) months, p = 0.015). The elective group of patients had significantly better overall survival compared to the emergent group (median of 36.7 (95% CI 30.7 to 42.7) versus 11.9 (95% CI 6.0 to 17.8) months, p = 0.01). Among the patients who underwent curative-intent procedures, there were no significant differences in overall or disease-free survival between elective and emergent groups. Despite the increased complexity of managing older patients, particularly in emergent cases, these findings emphasize the importance of elective, curative-intent surgeries to optimize overall survival. Effective treatment strategies and perioperative management tailored to this age group are essential for improving surgical outcomes and extending survival in elderly colon cancer patients.

A novel angiogenesis-associated risk score predicts prognosis and characterizes the tumor microenvironment in colon cancer.

Angiogenesis of the tumor microenvironment (TME) can promote the proliferation and metastases of colon cancer (CC). However, there is a lack of bioinformatics analysis to comprehensively clarify the molecular characteristics, immune interaction characteristics and predictive values of angiogenesis characteristics in CC patients. This study aimed to perform a comprehensive elucidation of the correlation between angiogenesis and CC for the purpose of improving the clinical management of CC. Angiogenesis-associated genes (AAGs) were evaluated in the population of CC patients from the Cancer Genome Atlas database and Gene Expression Omnibus dataset. The expression, prognostic role, and immune cell infiltration of AAGs were assessed first. And then we established the AAGs score to further explore the prognosis and treatment response of angiogenesis characteristics in individual patient. Totally, we identified two different molecular subtypes of angiogenesis, and there was a significant difference in the background of genome, expression profiles, prognosis, and characteristics of TME between two subtypes. And the AAGs score was independently associated with over survival in CC patients, the prognostic value was significant and confirmed in the entire cohort. And we also constructed a nomogram based on the risk score and clinical parameters to maximize the predictive ability of the risk score. Additionally, the AAGs score was significantly correlated with the tumor mutation burden score, cancer stem cell score and drug sensitivity. Our study elucidated the role of angiogenesis characteristics in CC and the AAGs score could help clinicians plan for individual management with chemotherapy agents and promote the development of immunotherapy in CC. Prospective studies need to be conducted to further confirm our findings.

Abstract 3130: In vitro characterization of a novel TROP2-targeting antibody-drug conjugate OBI-992

Abstract BACKGROUND TROP2, a transmembrane glycoprotein widely expressed on epithelial cancers, has emerged as an attractive target for antibody-drug conjugate (ADC) development. Sacituzumab govitecan, a TROP2 ADC conjugated to topoisomerase inhibitor (TOP1) SN-38, has been approved for patients with triple-negative breast cancer. This study aims to investigate the characteristics of a novel TROP2 antibody (R4702) and its ADC OBI-992, which is derived from the conjugation of R4702 with a TOP1 inhibitor exatecan. METHODS Clinical study: Prognostic roles of TROP2 and TOP1 in patients were accessed through the “Kaplan-Meier plotter” database from more than 1055 colon cancer patients. In vitro study: An ELISA study was conducted to investigate the binding epitope of R4702. Cell binding assay and Surface Plasmon Resonance were carried out to measure non-specific binding activity and binding affinity, respectively. DNA damage activity, cytotoxicity, and immunogenic cell death (ICD) effects of three TOP1 inhibitors exatecan, deruxtecan (Dxd), and SN-38, were evaluated. Cytotoxicity of OBI-992 along with other ADC was measured in both 2D and 3D spheroids cancer cells (gastric cancer NCI-N87, pancreatic cancer Capan1, and prostate cancer DU145). TROP2 and BCRP expression as well as potential mutations in TOP1 were investigated in TROP2 ADCs-induced resistant colon cancer cells. The synergistic effects of the combination of OBI-992 with PARP inhibitors were evaluated. RESULTS Clinical study: Positive correlations between high mRNA expressions of both TROP2 (p=0.0075) and TOP1 (p=0.043) with poor overall survival for colon cancer patients were found. In vitro: The R4702 antibody displayed different binding epitopes from sacituzumab and datopotamab. In addition, R4702 showed lower non-specific binding and better binding affinity to TROP2 antigen than datopotamab. The payload exatecan demonstrated excellent ICD effects. Relatively higher cytotoxicity was observed by exatecan when compared to that of Dxd and SN-38. OBI-992 exhibited excellent activities on cell growth inhibition in 2D cell cultures and 3D cell spheroids. TROP2 down-regulation and BCRP upregulation were not found in OBI-992-induced resistant cells. A mutation R364H was identified in TOP1 in the resistance study with OBI-992, which is critical for the binding to TOP1 inhibitors camptothecin analogs. Finally, a synergistic effect of OBI-992 and PARP inhibitors (talazoparib, rucaparib, niraparib, and olaparib) on the enhancement of cancer cell killing and DNA damage was observed. CONCLUSION High expression of both TROP2 and TOP1 is associated with poor survival in patients with colon cancer. R4702 is a novel TROP2 antibody with a unique binding epitope and low non-specific binding. Exatecan and exatecan-conjugated ADC OBI-992 showed high cytotoxic activities. Combination of OBI-992 with PARP inhibitors have potential in TROP2-expressing malignancies. Citation Format: Tzer-Min Kuo, Ting-Yu Chang, Jye-Yu Huang, Wei-Chien Tang, Chun-Jung Lin, Yi-Chen Wu, Chi-Huan Lu, Hao-Cheng Weng, Yu-Jung Chen, Yu-Hsuan Tsao, Cheng-Yen Wei, Lifen Shen, Wan-Fen Li, Ming-Tain Lai. In vitro characterization of a novel TROP2-targeting antibody-drug conjugate OBI-992 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3130.

Choice of baseline hazards in joint modeling of longitudinal and time-to-event cancer survival data.

Longitudinal time-to-event analysis is a statistical method to analyze data where covariates are measured repeatedly. In survival studies, the risk for an event is estimated using Cox-proportional hazard model or extended Cox-model for exogenous time-dependent covariates. However, these models are inappropriate for endogenous time-dependent covariates like longitudinally measured biomarkers, Carcinoembryonic Antigen (CEA). Joint models that can simultaneously model the longitudinal covariates and time-to-event data have been proposed as an alternative. The present study highlights the importance of choosing the baseline hazards to get more accurate risk estimation. The study used colon cancer patient data to illustrate and compare four different joint models which differs based on the choice of baseline hazards [piecewise-constant Gauss-Hermite (GH), piecewise-constant pseudo-adaptive GH, Weibull Accelerated Failure time model with GH & B-spline GH]. We conducted simulation study to assess the model consistency with varying sample size (N = 100, 250, 500) and censoring (20 %, 50 %, 70 %) proportions. In colon cancer patient data, based on Akaike information criteria (AIC) and Bayesian information criteria (BIC), piecewise-constant pseudo-adaptive GH was found to be the best fitted model. Despite differences in model fit, the hazards obtained from the four models were similar. The study identified composite stage as a prognostic factor for time-to-event and the longitudinal outcome, CEA as a dynamic predictor for overall survival in colon cancer patients. Based on the simulation study Piecewise-PH-aGH was found to be the best model with least AIC and BIC values, and highest coverage probability(CP). While the Bias, and RMSE for all the models showed a competitive performance. However, Piecewise-PH-aGH has shown least bias and RMSE in most of the combinations and has taken the shortest computation time, which shows its computational efficiency. This study is the first of its kind to discuss on the choice of baseline hazards.

Expression Analysis of VPS72 and Associated Biological Behaviors in Colon Cancer.

VPS72 is highly expressed in hepatocellular carcinoma and prostate cancer, participating in various cellular processes such as gene transcription, replication, DNA repair, maintenance of genome integrity, and cancer progression. However, its role in colorectal cancer remains unknown. Bioinformatic methods were used to analyze gene expression, correlation and patient survival. Western blotting, colony formation assays and animal experiments were used to evaluate the function of VPS72 in colon cancer in vivo and in vitro. VPS72 was highly expressed in colon cancer tissues and correlated with poor overall survival (P<0.05) and relapse free survival (P<0.01). Furthermore, patients with III/IV clinical stage (P<0.001), N1 nodal metastasis (P<0.001) or N2 nodal metastasis (P<0.05) status had poor overall survival. Further analysis showed that VPS72 is correlated with proliferation and EMT biomarkers. Western blotting, colony formation assays and animal experiments showed that VPS72 overexpression promoted colon cancer proliferation and EMT progress. Our study found that VPS72 was correlated with poor overall survival in colon cancer patients, and high expressed level of VPS72 promoted colon cancer progression, indicating its role as a potential prognosis biomarker.

Apigenin exerts anti-cancer effects in colon cancer by targeting HSP90AA1

Apigenin, a flavonoid, has shown early promise in colon cancer (CC); thus, exploring potential mechanisms of Apigenin is obligatory. In this study, shared targets of Apigenin and CC were identified through online tools, which were then subjected to functional enrichment analyses, Gene Ontology and KEGG. Further, the protein-protein interaction network of the shared targets was developed (via STRING). The top targets of Apigenin in CC were identified by molecular docking; further investigated for differential gene and protein expression in CC and their influence on CC patient survival (using TCGA data). Out of 13 hub genes, the top 3 targets (HSP90AA1, MMP9, PTGS2) were selected based on docking score. Their expression was significantly elevated and related to poor overall survival in CC (except PTGS2). Molecular dynamics simulation further validated protein-ligand interactions and divulged HSP90AA1 as the best target of Apigenin in CC. Finally, the anti-cancer effects of Apigenin and its major metabolite, luteolin, were investigated in CC, which is involved in the cytotoxicity of CC cells (COLO-205) by reducing HSP90AA1 expression revealed by real-time PCR. Thus, HSP90AA1 was identified as one of the prime targets of Apigenin in CC, and Apigenin could be effective against CC. Communicated by Ramaswamy H. Sarma

Tight Junction Claudins and Occludin Are Differentially Regulated and Expressed in Genomically Defined Subsets of Colon Cancer.

Metastatic colon cancer remains incurable despite improvements in survival outcomes. New therapies based on the discovery of colon cancer genomic subsets could improve outcomes. Colon cancers from genomic studies with publicly available data were examined to define the expression and regulation of the major tight junction proteins claudins and occludin in genomic groups. Putative regulations of the promoters of tight junction genes by colon-cancer-deregulated pathways were evaluated in silico. The effect of claudin mRNA expression levels on survival of colon cancer patients was examined. Common mutations in colon-cancer-related genes showed variable prevalence in genomically identified groups. Claudin genes were rarely mutated in colon cancer patients. Genomically identified groups of colon cancer displayed distinct regulation of claudins and occludin at the mRNA level. Claudin gene promoters possessed clustered sites of binding sequences for transcription factors TCF4 and SMADs, consistent with a key regulatory role of the WNT and TGFβ pathways in their expression. Although an effect of claudin mRNA expression on survival of colon cancer patients as a whole was not prominent, survival of genomic subsets was significantly influenced by claudin mRNA expression. mRNA expression of the main tight junction genes showed differential regulation in various genomically defined subgroups of colon cancer. These data pinpoint a distinct role of claudins and pathways that regulate them in these subgroups and suggest that subgroups of colon cancer should be considered in future efforts to therapeutically target claudins.

ADT-OH synergistically enhanced the antitumor activity of celecoxib in human colorectal cancer cells.

Colorectal cancer is one of the most prevalent cancers in the world, but the research on its prevention, early diagnosis and treatment is still a major challenge in clinical oncology. Thus, there is a pressing requirement to find effective strategies to improve the survival of colon cancer patients. Celecoxib has been accounted to be an effective antitumor drug, but may exhibit significant side effects. In recent studies, 5-(4-hydroxyphenyl)-3H-1,2-dithiole-3-thione (ADT-OH), one of the most commonly used reagents for the synthesis of sustained-release H2 S donors, has also been reported to inhibit cancer progression by affecting processes such as cell cycle, angiogenesis, and apoptosis. Therefore, we evaluated the therapeutic effect of the combination of ADT-OH and celecoxib on colorectal cancer through in vitro and in vivo, hoping to achieve better therapeutic effect and reduce the effect of celecoxib on gastric injury through exogenous administration of H2 S. Our results demonstrated that ADT-OH combined with celecoxib synergistically inhibited the proliferation and migration ability of human colorectal cancer HCT116 cells, altered cell cycle and cytoskeleton, increased intracellular reactive oxygen species (ROS), and promoted cell apoptosis. Noteworthy, in vivo studies also indicated the excellent antitumor therapeutic effect of the combination therapy without apparent toxicity. In general, our results provide a reasonable combination strategy of low-dose ADT-OH and celecoxib in the preclinical application of colorectal cancer.

Exploring Cancer Dependency Map genes and immune subtypes in colon cancer, in which TIGD1 contributes to colon cancer progression.

Tumour-dependent genes identified in CRISPR-Cas9 screens have been widely reported in Cancer Dependency Maps (CDMs). CDM-derived tumour-dependent genes play an important role in tumorigenesis and progression; however, they have not been investigated in colon cancer (CC). CDM genes overexpressed in CC were identified from the TCGA-COAD dataset and CDM platform. A CDM signature and prognostic nomogram were constructed by Lasso Cox regression and multivariate Cox analyses. A weighted correlation network analysis (WGCNA) and consensus clustering were used to define coexpressed genes with CDM risk scores and to determine two new immune subtypes. A comprehensive investigation was performed between the two subtypes and immune regulation, the immune microenvironment and the impact of immunotherapy. First, 1304 overexpressed CDM genes were identified. Then, a CDM signature with five cancer-dependent genes (MMS19, NOP14, POLRMT, SNAPC5 and TIGD1) and a prognostic nomogram were constructed, and they demonstrated robust predictive performance and a close relationship with clinical characteristics in different CC datasets. Patients with high CDM risk scores showed worse survival outcome and weaker response to chemotherapy. Additionally, TIGD1 genes were oncogenes that affected the CC cell cycle, according to cell functional experiments that involved the suppression of the TIGD1 gene. Furthermore, WGCNA and consensus clustering were used to define coexpressed genes with CDM risk scores and to determine two new immune subtypes. Finally, systematic investigations were conducted with the relationship between the CDM subtypes and immune regulation. This study constructed a CDM signature consisting of five risk genes that predict survival in CC patients. In addition, the immune subtypes provided valuable insights into immunotherapy for CC patients. TIGD1, as an oncogene, is independent prognostic factors for CC, and contributes to CC progression.

Prognostic modeling of overall survival and analysis of K-M survival curves in patients with primary colon cancer: A SEER-based study.

This study aimed to establish a validated prognostic survival column line chart by analyzing data from patients with colon cancer (CC) in the SEER database. The nomogram proposed in this study was based on the retrospective data of patients diagnosed with CC in the SEER database from 1975 to 2015. Randomly divided into training and validation sets, the nomogram was constructed using the Cox model, and the discriminatory power of the nomogram and its predictive accuracy were determined using the consistency index and associated calibration curves. In a multifactorial analysis of the main cohort, the independent factors for survival were age, sex, race, tumor stage, and tumor grade, all of which were included in the nomogram and were prognostic factors for patients with CC (P < .05). The calibration curve of the survival probability showed good agreement between the prediction of the nomogram and the actual observation. The validation calibration curve showed good correlation and agreement between predicted and observed values. Multifactorial analysis showed that the factors affecting the prognosis of patients with CC included age, sex, race, tumor-node-metastasis stage, and tumor pathological stage. The nomogram prediction model proposed in this study has high accuracy and can provide more accurate prognostic prediction and relevant reference values for assessing the postoperative survival of CC patients and guiding clinical decision-making.

Deep learning tumor heterogeneity metric from histopathology images vs next generation sequencing-derived scores for colon cancer prognostication.

3537 Background: Tumor heterogeneity is as an important determinant of clinical behavior in many cancer types, with increased heterogeneity thought to confer inferior clinical outcome. Sequencing based assessment of colon cancer has been used to quantify tumor heterogeneity and correlate it with survival, but is sensitive to the mutation calling algorithm utilized. Digitization of histopathology slides allows application of deep learning methods for image analysis. Automated slide annotation and feature extraction provides numeric representations of underlying phenotype from which tumor heterogeneity can be estimated. Here we compare the ability of a deep-learning tumor heterogeneity score (THS) to estimate overall survival in colon cancer patients to estimates produced by bulk sequencing derived mutant-allele tumor heterogeneity (MATH) and copy number variation (CNV) event scores. Methods: Digitized whole slide images (WSIs) from The Cancer Genome Atlas (TCGA) colon adenocarcinoma dataset are processed in a computational pipeline for tissue detection, numerical feature extraction, and cell type classification. WSIs are tiled and local THS calculated from imaging features. Corresponding MATH and CNV derived heterogeneity metrics are calculated from published sequencing data. Kaplan Meier curves are used to compare patient survival stratified by tumor heterogeneity as calculated by the three independent methods. Automated regional annotation identifies intra-tumoral and tumor-stromal boundary tiles and tumor THS is correlated to distance from the boundary. Results: Images from 379 patients (209 right-sided, 152 left-sided tumors) yielded 575,762 tiles. Automated annotation resulted in 272,791 intra-tumoral and 11,340 tumor-stromal boundary tiles. Stratification by imaging derived THS provided significant separation of overall survival curves (p &lt; .01) in contrast to MATH and CNV methods (p &gt; .05 for both). THS significantly separated the curves in right- but not left-sided cancers (p = .03 and .44, respectively). Evaluating THS as a function of distance from the tumor-stromal boundary, right-sided tumors showed significant decrease in THS with increasing distance from tumor edge. Conclusions: Our novel pipeline produced spatially resolved imaging data informed by underlying tumor phenotype without need for pathologist annotation. The resultant THS correlated with outcome and outperformed sequencing-based prognostication methods. The spatial information identified higher heterogeneity at the tumor edge than interior regions of right-sided, but not left-sided tumors, capturing known but poorly understood differences in colon tumors by location. Deep learning image analysis provided reproducible and cost-effective data with great potential both in clinical biomarker discovery and as a research tool.

Homeobox B9 Promotes Colon Cancer Progression by Targeting SRSF3.

Homeobox B9 (HOXB9) is one of the HOX family of transcription factors that are essential for cancer development and embryonic growth. However, the clinical importance and biological involvement of HOXB9 in colon cancer (CC) are not adequately understood. To investigate whether HOXB9 participates in the proliferation, invasion, and migration of CC. This study investigated the function and clinical significance of HOXB9 mRNA and protein expression in CC. Furthermore, overexpression and knockdown experiments of HOXB9 were developed to explore their effects on CC cell transwell and proliferation. Moreover, a molecular mechanism of HOXB9 regulate serine/arginine-rich splicing factor 3 (SRSF3) was explored. HOXB9 expression was higher in CC cells and tissues at both the mRNA and protein levels. Poor survival in CC patients was significantly connected with high HOXB9 expression, which was also strongly associated with the TNM stage and lymph node metastases. Furthermore, in vitro CC cell proliferation, transwell were markedly aided by HOXB9 overexpression. Contrarily, HOXB9 knockdown had the reverse result and inhibited the formation of xenograft tumors in naked mice. Gene set enrichment analysis (GSEA)revealed a correlation between high HOXB9 expression and spliceosomes. JASPAR and GEPIA2.0, in addition to CHIP and dual-luciferase reporting assays, confirmed that HOXB9 targets the promoter of SRSF3 to enhance its expression. We also found that SRSF3 knockdown eliminated HOXB9 from cell proliferation and transwell. We characterized the function and mechanism of HOXB9 in regulating colon cancer growth, suggesting a novel molecular approach for colon cancer-targeted therapy.

18F-FDG PET/CT Image Deep Learning Predicts Colon Cancer Survival.

Colon cancer is a type of cancer that begins in the large intestine. In the process of efficacy evaluation, postoperative recurrence prediction and metastasis monitoring of colon cancer, traditional medical image analysis methods are highly dependent on the personal ability of the doctors. In the process of patient treatment, it not only increases the workload and work pressure for doctors, but also has some problems with traditional medical image analysis methods. Moreover, the traditional medical image analysis methods have problems such as insufficient prediction accuracy, slow prediction speed, and the risk of errors in prediction. When analyzing 18F-FDG PET/CT images by traditional medical image analysis methods, it is easy to cause problems such as untimely treatment plans and errors in diagnosis, which will adversely affect the survival of colon cancer patients. Although 18F-FDG PET/CT images have certain advantages in image clarity and accuracy compared with traditional medical imaging methods, the analysis method based on 18F-FDG PET/CT images also has certain effects in predicting the survival of colon cancer patients, but there are still many shortcomings: the 18F-FDG PET/CT image analysis method overly relies on the technical advantages of 8F-FDG PET/CT images; in the analysis and prediction of image data, it has not gotten rid of the dependence on the personal medical quality of the doctors; traditional medical image analysis methods are still used when analyzing and predicting images; there is no breakthrough in image analysis effects. In order to solve these problems, this paper combined deep learning theory, using three algorithms of the improved RBM algorithm, image feature extraction method based on deep learning, and regression neural network to analyze and predict 18F-FDG PET/CT images, and applied some algorithms to analyze and predict 18F-FDG PET/CT images, and also established a deep learning-based 18F-FDG PET/CT image survival analysis prediction model. Four aspects survival prediction accuracy, survival prediction speed, survival prediction precision, and physician satisfaction were studied through this model. The research results have shown that compared with traditional medical image analysis methods, the prediction accuracy of 18F-FDG PET/CT image survival analysis prediction model based on deep learning is improved by 0.83%, and the prediction speed is improved by 3.42%, as well as the prediction precision increased by 6.13%. The research results show that the deep learning-based 18F-FDG PET/CT image survival analysis prediction model established in this paper is of great significance to improve the survival rate of colon cancer patients, and also promotes the development of the medical industry.

Significance of logistic regression scoring model based on natural killer cell-mediated cytotoxic pathway in the diagnosis of colon cancer.

The poor clinical accuracy to predict the survival of colon cancer patients is associated with a high incidence rate and a poor 3-year survival rate. This study aimed to identify the poor prognostic biomarkers of colon cancer from natural killer cell-mediated cytotoxic pathway (NKCP), and establish a logistical regression scoring model to predict its prognosis. Based on the expressions and methylations of NKCP-related genes (NRGs) and the clinical information, dimensionality reduction screening was performed to establish a logistic regression scoring model to predict survival and prognosis. Risk score, clinical stage, and ULBP2 were used to establish a logistic regression scoring model to classify the 3-year survival period and compare with each other. Comparison of survival, tumor mutation burden (TMB), estimation of immune invasion, and prediction of chemotherapeutic drug IC50 were performed between low- and high-risk score groups. This study found that ULBP2 was significantly overexpressed in colon cancer tissues and colon cancer cell lines. The logistic regression scoring model was established to include six statistically significant features: S = 1.70 × stage - 9.32 × cg06543087 + 6.19 × cg25848557 + 1.29 × IFNA1 + 0.048 × age + 4.37 × cg21370856 - 8.93, which was used to calculate risk score of each sample. The risk scores, clinical stage, and ULBP2 were classified into three-year survival, the 3-year prediction accuracy based on 10-fold cross-validation was 80.17%, 67.24, and 59.48%, respectively. The survival time of low-risk score group was better than that of the high-risk score group. Moreover, compared to high-risk score group, low-risk score group had lower TMB [2.20/MB (log10) vs. 2.34/MB (log10)], higher infiltration score of M0 macrophages (0.17 vs. 0.14), and lower mean IC50 value of oxaliplatin (3.65 vs 3.78) (p < 0.05). The significantly upregulated ULBP2 was a poor prognostic biomarker of colon cancer. The risk score based on the six-feature logistic regression model can effectively predict the 3-year survival time. High-risk score group demonstrated a poorer prognosis, higher TMB, lower M0 macrophage infiltration score, and higher IC50 value of oxaliplatin. The six-feature logistic scoring model has certain clinical significance in colon cancer.

ULBP2 is a biomarker related to prognosis and immunity in colon cancer.

The study aimed to determine whether ULBP2 was associated with prognosis and immune infiltration in colon cancer (CC) and provided important molecular basis inorderto early non-invasive diagnosis and immunotherapy of CC. Using The Cancer Genome Atlas database (TCGA) and ImmPort database, we extracted messenger RNA (mRNA) data of CC and immune-related genes, then we used "limma" package, "survival" package, and Venn overlap analysis to obtain the differentially expressed mRNA (DEmRNA) associated with prognosis and immunity of CC patients. "pROC" package was used to analyze receiver operating characteristics (ROC) of target gene. We used chi-square test and two-class logistics model to identify clinicopathological parameters that correlated with target gene expression. In order to determine the effects of target gene expression and clinicopathological parameters on survival, univariate and multivariate cox regression analyses were performed. We analyzed the related functions and signaling pathways of target gene by enrichment analysis. Finally, the correlation between target gene and tumor immune infiltrating was explored by ssGSEA and spearman correlation analysis. Results showed that ULBP2 was a target gene associated with immunity and prognosis in CC patients. CC patients with higher ULBP2 expression had poor outcomes. In terms of ROC, ULBP2 had an area under the curve (AUC) of 0.984. ULBP2 was associatedwith T stage, N stage, and pathologic stage of CC patients, and served as an independent predictor of overall survival in CC patients. Functional enrichment analysis revealed ULBP2 was obviously enriched in pathways connected with carcinogenesis and immunosuppression. The expression of ULBP2 was significantly associated with tumor immune cells and immune checkpoints according to ssGSEA and spearman correlation analysis. To conclude, our study suggested that ULBP2 was associated with tumor immunity, and might be a biomarker associated with the diagnosis and prognosis of CC patients, and a potential target of CC immunotherapy.

Prognostic Factors of Disease Recurrence and Overall Survival Following Curative Resection of Colon Cancer: A 10-year Cohort from a Referral Center.

Background: The growing incidence of colorectal cancer around the world highlights the significance of tumor recurrence and patient survival as 2 key elements of patient therapy. We aimed to study the factors linked with disease recurrence and survival in colon cancer. Methods: Patients with colon cancer who underwent tumor excision as their primary treatment were enrolled in this prospective cohort and monitored for 10 years. Various demographic and clinicopathologic factors of these patients were studied in association with the 2 primary outcomes of this study, including tumor recurrence and patient survival. Statistical tests and survival analysis were utilized to explore the study aims. Results: An overall number of 113 patients were included in this survey with a mean age of 54.7 (±SD, 14.1), and most of the patients were men (56.6%). The mean follow-up period was 28.3 (±25.5) months. Tumor recurrence occurred in 32 (28.3%) patients in the study period. The estimated mean survival of patients was 54.9 (95% CI, 45.3-64.4) months. N staging ( p = 0.036), T staging ( p = 0.009), and pathologic staging (P = .004) were the significant pathological factors to higher tumor recurrence and lower survival rates. Conclusion: Advanced tumor staging led to increased disease recurrence and lower survival of colon cancer patients in this survey. Further public health screening and education programs are needed to improve the early detection and prognosis of these patients in Iran.