Construction of a CXC Chemokine-Based Prediction Model for the Prognosis of Colon Cancer

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

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Recent Insights into the Roles of PEST-Containing Nuclear Protein

PEST-containing nuclear protein (PCNP), a short-lived small nuclear protein with 178 amino acids, is a nuclear protein containing two PEST sequences. PCNP is highly expressed in several malignant tumors such as cervical cancer, rectal cancer, and lung cancer. It is also associated with cell cycle regulation and the phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) and Wnt signaling pathways during tumor growth. The present article discuss how PCNP regulates the PI3K/AKT/mTOR and Wnt signaling pathways and related proteins, and the ubiquitination of PCNP regulates tumor cell cycle as well as the progress of the application of PCNP in the pathophysiology and treatment of colon cancer, human ovarian cancer, thyroid cancer, lung adenocarcinoma and oral squamous cell carcinoma. The main relevant articles were retrieved from PubMed, with keywords such as PEST-containing nuclear protein (PCNP), cancer (tumor), and signaling pathways as inclusion/exclusion criteria. Relevant references has been included and cited in the manuscript.

Comprehensive Pan-Cancer Analysis of Connexin 43 as a Potential Biomarker and Therapeutic Target in Human Kidney Renal Clear Cell Carcinoma (KIRC)

Background and Objectives: Connexin 43 (Cx43) is involved in the transfer of small signaling molecules between neighboring cells, thereby exerting a major influence on the initiation and progression of tumorigenesis. However, there is a lack of systematic research on Cx43 expression and its predictive role in clinical diagnosis and prognosis in pan-cancer. Materials and Methods: Several biological databases were used to evaluate the expression levels of GJA1 (encoding Cx43) and its diagnostic and prognostic significance in pan-cancer. We targeted kidney renal clear cell carcinoma (KIRC) and investigated the relationship between GJA1 expression and different clinical features of KIRC patients. Then, we performed cell-based experiments to partially confirm our results and predicted several proteins that were functionally related to Cx43. Results: The expression of GJA1 has a high level of accuracy in predicting KIRC. High GJA1 expression was remarkably correlated with a favorable prognosis, and this expression was reduced in groups with poor clinical features in KIRC. Cell experiments confirmed the inhibitory effects of increased GJA1 expression on the migratory capacity of human renal cancer (RCC) cell lines, and protein-protein interaction (PPI) analysis predicted that CDH1 and CTNNB1 were closely related to Cx43. Conclusions: GJA1 could be a promising independent favorable prognostic factor for KIRC, and upregulation of GJA1 expression could inhibit the migratory capacity of renal cancer cells.

Exploring Immune-Related Gene Profiling and Infiltration of Immune Cells in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Cervical cancer is a widespread malignancy among women, leading to a substantial global health impact. Despite extensive research, our understanding of the basic molecules and pathogenic processes of cervical squamous cell carcinoma is still insufficient. This investigation aims to uncover immune-related genes linked to CESC and delineate their functions. Leveraging data from the GEO and ImmPort databases, a total of 22 immune-related genes were identified. Multiple tools, including DAVID, the human protein atlas, STRING, GeneMANIA, and TCGA, were employed to delve into the expression and roles of these immune genes in CESC, alongside their connections to the disease's pathological features. Through RT-PCR, the study confirmed notable disparities in CXCL8 and CXCL10 mRNA expression between CESC and normal cervical tissue. The TCGA dataset's immune-related information reinforced the association of CXCL8 and CXCL10 with immune infiltration in CESC. This research sheds light on the potential of CXCL8 and CXCL10 as promising therapeutic targets and essential prognostic factors for individuals diagnosed with CESC.

Leveraging a KRAS-based signature to predict the prognosis and drug sensitivity of colon cancer and identifying SPINK4 as a new biomarker

KRAS is one of the leading mutations reported in colon cancer. However, there are few studies on the application of KRAS related signature in predicting prognosis and drug sensitivity of colon cancer patient. We identified KRAS related differentially expressed genes (DEGs) using The Cancer Genome Atlas (TCGA) database. A signature closely related to overall survival was recognized with Kaplan-Meier survival analysis and univariate cox regression analysis. Then we validated this signature with overall expression score (OE score) algorithm using both scRNA-seq and bulk RNA-seq data. Based on this signature, we performed LASSO cox regression to establish a prognostic model, and corresponding scores were calculated. Differences in genomic alteration, immune microenvironment, drug sensitivity between high- and low-KRD score groups were investigated. A KRAS related signature composed of 80 DEGs in colon cancer were recognized, among which 19 genes were selected to construct a prognostic model. This KRAS related signature was significantly correlated with worse prognosis. Furthermore, patients who scored lower in the prognostic model presented a higher likelihood of responding to chemotherapy, targeted therapy and immunotherapy. Furthermore, among the 19 selected genes in the model, SPINK4 was identified as an independent prognostic biomarker. Further validation in vitro indicated the knockdown of SPINK4 promoted the proliferation and migration of SW48 cells. In conclusion, a novel KRAS related signature was identified and validated based on clinical and genomic information from TCGA and GEO databases. The signature was proved to regulate genomic alteration, immune microenvironment and drug sensitivity in colon cancer, and thus might serve as a predictor for individual prognosis and treatment.

A novel 5-gene prognostic signature to improve risk stratification of cytogenetically normal acute myeloid leukemia

PURPOSE

Prognostic prediction is a challenging task in cytogenetically normal acute myeloid leukemia (CN-AML) patients. In this study, we aimed at developing a novel prognostic signature to predict and stratify the survival of CN-AML patients.

METHODS

Using a training dataset (GSE12417), 5-gene prognostic signature was established to predict survival of CN-AML patients. The prognostic performance of this prognostic signature was further validated in testing dataset (TCGA CN-AML cohort) and validation dataset (GSE6891 CN-AML cohort).

RESULTS

In training, testing and validation datasets, the increased 5-gene risk score was significantly related with inferior overall survival (OS) of patients, and the area under the receiver operating characteristic curve (AUC) demonstrated that our prognostic signature had overall prediction accuracy. The excellent prognostic value of the 5-gene prognostic signature was also supported by the comparison with three previously proposed prognostic models. For the intermediate-risk CN-AML patients and the CN-AML patients with FLT3 or NPM1 mutation, our model could also well dichotomize them into two subgroups with distinct prognosis. Multivariate analysis demonstrated that 5-gene risk score was the only independent risk factor in TCGA CN-AML cohort. Nomogram including the 5-gene risk score performed well in predicting 1-year, 2-year and 3-year OS.

CONCLUSION

In summary, our novel 5-gene prognostic signature facilitated the improvement in risk stratification of CN-AML patients.

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

Background

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.

Methods

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.

Results

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).

Conclusions

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.

Alterations in Gene Pair Correlations as Potential Diagnostic Markers for Colon Cancer

Colorectal cancer (CRC) is a leading cause of death from cancer in Canada. Early detection of CRC remains crucial in managing disease prognosis and improving patient survival. It can also facilitate prevention, screening, and treatment before the disease progresses to a chronic stage. In this study, we developed a strategy for identifying colon cancer biomarkers from both gene expression and gene pair correlation. Using the RNA-Seq dataset TCGA-COAD, a panel of 71 genes, including the 20 most upregulated genes, 20 most downregulated genes and 31 genes involved in the most significantly altered gene pairs, were selected as potential biomarkers for colon cancer. This signature set of genes could be used for early diagnosis. Furthermore, this strategy could be applied to other types of cancer.

Effect and Prognosis Factors of Combining Laparoscopic Radical Resection of Colon Adenocarcinoma with Docetaxel Therapy in Treating Middle and Advanced Colon Adenocarcinoma

Objective. The aim of the study is to explore the clinical efficacy and prognosis factors of joint application of laparoscopic radical resection of colon adenocarcinoma (COAD) and docetaxel therapy in treating COAD of middle and advanced stages. Methods. The clinical data of 103 COAD patients of middle and advanced stages treated in our hospital from July 2016 to July 2018 were selected for the retrospective analysis, all patients received the treatment scheme of combining laparoscopic radical resection of COAD with docetaxel therapy for the observation of short-term efficacy, follow-up was conducted to record their 3-year survival, and relevant factors affecting patient prognosis were analyzed by the logistic regression model. Results. After treatment, the total remission rate of patients was 75.73% (78/103), the total incidence rate of adverse reactions was 16.50% (17/103); patients’ level values of various serum tumor markers after treatment were significantly lower than those before treatment ( $P<0.001$ ); according to the univariate analysis results, for COAD patients with different tumor diameters, differentiated degrees, TNM stages, perineural invasion degrees, pathological types, and depths of invasion, their modality rates were statistically different ( $P<0.05$ ); and the logistic regression analysis showed that tumor diameter ≥5 cm, poor differentiation, TNM stage IV, perineural invasion, pathologically signet-ring cell carcinoma, and T3-invasion were the independent risk factors affecting patient prognosis ( $P<0.05$ ). Conclusion. Combining laparoscopic radical resection of COAD with docetaxel therapy in treating COAD of middle and advanced stages achieves affirmed short-term efficacy, which can reduce patients’ level of serum tumor markers and ensure high safety and good survival prognosis. Tumor diameter, differentiated degree, TNM stage, perineural invasion, pathological type, and T3-invasion are the relevant factors affecting the prognosis of middle and advanced COAD.

Long non-coding RNA LINC00511 facilitates colon cancer development through regulating microRNA-625-5p to target WEE1

The altered part of long non-coding RNA LINC00511 (LINC00511) is extensively discussed in malignancies. Finitely, the mechanism of LINC00511 in colon cancer (CC) development lacks thorough explorations. Hence, this work is started from the LINC00511-mediated microRNA (miR)-625-5p/WEE1 axis in the CC process. LINC00511, miR-625-5p, and WEE1 levels were tested in CC tissues and cells. Subcellular localization of LINC00511 was clarified. CC cells were transfected with oligonucleotides that altered LINC00511, and miR-625-5p expression to define their performance in CC cell progression. The tumorigenic ability of cells was verified in xenografted tumors. CC tissues and cells highly expressed LINC00511 and WEE1 and lowly expressed miR-625-5p. LINC00511 was mainly localized in the cytoplasm. Deleted LINC00511 or restored miR-625-5p delayed cellular growth in CC. LINC00511 sponged miR-625-5p to target WEE1. Silenced miR-625-5p mitigated the role of depleted LINC00511, while inhibited WEE1 rescued the effect of silenced miR-625-5p on the biological functions of CC cells. It is summarized that down-regulated LINC00511 obstructs tumorigenesis of CC through restoring miR-625-5p and silencing WEE1, consolidating a basal reference for CC-oriented therapy.

LINC00858 promotes colon cancer progression through activation of STAT3/5 signaling by recruiting transcription factor RAD21 to upregulate PCNP

The purpose of our investigation is to explore the putative molecular mechanisms underpinning LINC00858 involvement in colon cancer. The expression of LINC00858 in TCGA data was identified using the GEPIA website. Colon cancer cancerous tissues were clinically collected. The expression of LINC00858, RAD21, and PCNP in colon tissues or cells was determined using RT-qPCR. The interactions among LINC00858, RAD21, and PCNP promoter region were determined by means of RNA pull down, RIP, and ChIP assays. Cell proliferative, apoptotic, invasive, and migrated capabilities were evaluated. Western blot was conducted to determine RAD21, PCNP, phosphorylated (p)-STAT3, STAT3, p-STAT5 and STAT5 and apoptosis related proteins. A nude mouse model of colon cancer was constructed and tumorigenesis of colon cancer cells was observed. LINC00858 was upregulated in cancerous tissues and cells. LINC00858 recruited the transcription factor RAD21. Overexpression of LINC00858 promoted the binding of RAD21 and PCNP promoter region, which increased the expression of PCNP. Silencing of RAD21 or PCNP reversed the promoting effect of LINC00858 on the disease initiation and development. PCNP silencing inhibited proliferative ability and promoted apoptotic ability of cancerous cells via STAT3/5 inhibition, which was reversed by colivelin-activated STAT3. In vivo experiments further verified that LINC00858 enhanced the tumorigenicity of colon cancer cells in vivo by regulating the RAD21/PCNP/STAT3/5 axis. It indicated the promoting role of LINC00858 in colon cancer progression though activating PCNP-mediated STAT3/5 pathway by recruiting RAD21.

Exploration of potential therapeutic and prognostic value of CXC chemokines in cervical squamous cell carcinoma and endocervical adenocarcinoma based on bioinformatics analysis

Cervical cancer, as the second most common female malignancy, brings a great health burden to women worldwide. Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are the most common histological subtypes of cervical cancer. CXC chemokines (CXCLs) within the tumor microenvironment can modulate carcinogenesis and progression. The present study aimed to explore the therapeutic and prognostic value of different CXCLs in CESC. ONCOMINE, GEPIA, cBioPortal, TRRUST, GeneMANIA, STRING and TIMER were utilized to explore the expression, mutation and function of CXCLs in CESC, as well as their correlation with pathological and survival features of CESC patients. We found that the mRNA expression levels of CXCL1/8/9/10/11/13/16/17 in CESC were upregulated compared with normal cervical tissues, whereas CXCL12 was downregulated. No significant correlation was found between the expression levels and pathological stage of CESC patients. CESC patients with high expression of CXCL1/2/3/4/5/8 were significantly associated with poor overall survival, additionally, low mRNA level of CXCL3 was associated with better disease-free survival. Besides, a high mutation rate (43%) of CXCLs in CESC was observed. Depicted by co-expression analysis, the expression of CXCL1/2/3/6/8 showed a modest to strong correlation, while that of CXCL9/10/11/13 showed a very strong correlation. Differentially expressed CXCLs primarily functioned in chemokine signaling pathway and inflammation response, such as cell chemotaxis, chemokine activity and chemokine receptor binding. We also found the association of CXCLs with the tumor-infiltration of six types of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells) in CESC patients. The present study elucidated that CXCLs may have the potential to be novel therapeutic targets and prognosis predictors of CESC patients.

CXCL11 Correlates With Antitumor Immunity and an Improved Prognosis in Colon Cancer

The chemokine ligand C-X-C motif chemokine ligand 11 (CXCL11) is involved in the progression of various cancers, but its biological roles in colorectal cancer (CRC) remain confused. Therefore, the prognostic value and underlying mechanism of CXCL11 in CRC were preliminarily evaluated. Three independent datasets were used for mRNA-related analysis: one dataset from the Cancer Genome Atlas (TCGA, n = 451) and two single-cell RNA sequencing (scRNA-seq) datasets from Gene Expression Omnibus (GEO): GSE146771 and GSE132465. In addition, a colon adenocarcinoma (COAD) patient cohort (the Yijishan Hospital cohort, YJSHC, n = 108) was utilized for analysis of cell infiltration by immunohistochemistry. We determined the distribution of CXCL11 in tumor tissue across all TCGA cancers and found that CXCL11 expression was significantly upregulated in both COAD and rectal adenocarcinoma (READ). However, the upregulation of CXCL11 mRNA was associated with a better prognosis in COAD, but not in READ. Within the YJSHC, the patients with a high abundance of intratumoral CXCL11⁺ cells had prolonged survival (p = 0.001). Furthermore, we found that the high CXCL11 expression group had a higher proportion of antitumor immune cells, and a lower proportion of protumor immune cells. Additionally, we discovered the changes of gene expression and enriched immune pathway network mediated by CXCL11. Interestingly, both cytotoxic genes (IFNG, GZMA, GZMB, GZMK, GZMM, and PRF1) and immunosuppressive molecules, including PD-L1, were positively correlated with CXCL11 expression. CXCL11, which promoted antitumor immunity to benefit survival, was identified as an independent prognostic biomarker in patients with COAD.

Clinical and genomic characteristics of metabolic syndrome in colorectal cancer

Metabolic syndrome (MetS) is characterized by a group of metabolic disturbances which leads to the enhanced risk of cancer development. Elucidating the mechanisms between these two pathologies is essential to identify the potential therapeutic molecular targets for colorectal cancer (CRC). 716 colorectal patients from the First and Second Affiliated Hospital of Wenzhou Medical University were involved in our study and metabolic disorders were proven to increase the risk of CRC. The prognostic value of the MetS factors was analyzed using the Cox regression model and a clinical MetS-based nomogram was established. Then by using multi-omics techniques, the distinct molecular mechanism of MetS genes in CRC was firstly systematically characterized. Strikingly, MetS genes were found to be highly correlated with the effectiveness of targeted chemotherapy administration, especially for mTOR and VEGFR pathways. Our results further demonstrated that overexpression of MetS core gene IL6 would promote the malignancy of CRC, which was highly dependent on mTOR-S6K signaling. In conclusion, we comprehensively explored the clinical value and molecular mechanism of MetS in the progression of CRC, which may serve as a candidate option for cancer management and therapy in the future.

Serum Chemokine CXCL7 as a Potential Novel Biomarker for Obstructive Colorectal Cancer

Due to the lack of typical symptoms and signs and sensitive indicators for early diagnosis of obstructive colorectal cancer (OCRC), it is critically needed to find new novel biomarkers to ameliorate the management of OCRC patients. In this study, 472 blood samples were collected and measured by enzyme-linked immunosorbent assay (ELISA) to investigate the value of serum chemokine ligand 7 (CXCL7) in diagnosis and prognosis for OCRC patients. The median concentrations of CXCL7 in non-OCRC and OCRC were both higher than that in controls (both P < 0.05). Importantly, the median serum concentration of CXCL7 in OCRC was also higher than that in non-OCRC (P < 0.001). In all OCRC patients, the area under the curve (AUC) of CXCL7 was 0.918 with a sensitivity of 86.54% and a specificity of 81.87%. Similarly, the AUC of CXCL7 was 0.684 when the diagnostic test was performed between OCRC and CRC patients. CXCL7 had a higher AUC than other markers. The concentration of CXCL7 in 40 postoperative OCRC patients was higher than normal people and lower than preoperative patients. The median survival time was 62.00 months and the 5-year overall survival (OS) rate of the patients was 51.80% in all 155 OCRC patients. Multivariate Cox proportional hazard regression model analysis showed that high CXCL7 in serum was independent factors associated with poor OS of OCRC patients (HR = 2.216, P = 0.032). These results demonstrate that serum CXCL7 may be a potential biomarker both in diagnosis and prognosis for OCRC patients.

Derivation and Validation of a Prediction Model for Predicting the 5-Year Incidence of Type 2 Diabetes in Non-Obese Adults: A Population-Based Cohort Study

PURPOSE

The aim of this study was to derivate and validate a nomogram based on independent predictors to better evaluate the 5-year risk of T2D in non-obese adults.

PATIENTS AND METHODS

This is a historical cohort study from a collection of databases that included 12,940 non-obese participants without diabetes at baseline. All participants were randomised to a derivation cohort (n = 9651) and a validation cohort (n = 3289). In the derivation cohort, the least absolute shrinkage and selection operator (LASSO) regression model was used to determine the optimal risk factors for T2D. Multivariate Cox regression analysis was used to establish the nomogram of T2D prediction. The receiver operating characteristic (ROC) curve, C-index, calibration curve, and decision curve analysis were performed by 1000 bootstrap resamplings to evaluate the discrimination ability, calibration, and clinical practicability of the nomogram.

RESULTS

After LASSO regression analysis of the derivation cohort, it was found that age, fatty liver, γ-glutamyltranspeptidase, triglycerides, glycosylated hemoglobin A1c and fasting plasma glucose were risk predictors, which were integrated into the nomogram. The C-index of derivation cohort and validation cohort were 0.906 [95% confidence interval (CI), 0.878-0.934] and 0.837 (95% CI, 0.760-0.914), respectively. The AUC of 5-year T2D risk in the derivation cohort and validation cohort was 0.916 (95% CI, 0.889-0.943) and 0.829 (95% CI, 0.753-0.905), respectively. The calibration curve indicated that the predicted probability of nomogram is in good agreement with the actual probability. The decision curve analysis demonstrated that the predicted nomogram was clinically useful.

CONCLUSION

Our nomogram can be used as a reasonable, affordable, simple, and widely implemented tool to predict the 5-year risk of T2D in non-obese adults. With this model, early identification of high-risk individuals is helpful to timely intervene and reduce the risk of T2D in non-obese adults.

Targeting STAT proteins via computational analysis in colorectal cancer

Colorectal cancer (CRC) is the third most common cancer diagnosed worldwide making it a serious global challenge. CRC progression results from dysregulated cytoplasmic transcription factors, including signal transducer and activator of transcription (STAT) proteins that are involved in JAK-STAT pathway. The STAT proteins contain a conserved SH2 domain that facilitates the initiation of STAT activation via binding to tyrosine motifs followed by STAT dimerization. The STAT proteins include STAT1, STAT2 and STAT3 which all facilitate therapeutic targets for many drugs, since they are associated with pathogenesis in various cancers such as CRC. Genistein is an efficient chemopreventive phytochemical drug against CRC. The current investigation presents a computational study performed to investigate the molecular interaction between STAT1, STAT2 and STAT3 proteins with genistein. The molecular dynamic simulation was conducted for STAT2 protein. The studies from molecular docking revealed that the interaction of STAT proteins and genistein is predicted to be effective with better binding energies. Furthermore, targeting STAT3 could be an efficient therapeutic target and understanding the interaction between STAT3 and genistein can help to contribute to a better inhibition process for CRC progression. Treatment with genistein led to significant suppression of cell proliferation and STAT3 protein expression in both CRC (HCT 116 and HT-29) cell lines. This further provides development of efficient STAT inhibitors with better potency and bioavailability.