Colorectal Cancer Samples Research Articles

Subtyping colorectal cancer based on septic shock-associated genes: prognosis and immune characteristics

BackgroundSepsis and colorectal cancer (CRC) are leading causes of death. Given their mutual dependence for susceptibility, we used bioinformatics to explore potential connections between septic shock (SS) and CRC.MethodsWe identified 452 co-expressed genes between SS-related differential expression genes (SS-DEGs) and CRC patient-expressed genes (TCGA-CRC genes). CRC samples were categorized into two cluster subgroups through hierarchical clustering. We then compared the prognosis and immune landscapes of the two cluster subgroups through survival analysis, immune microenvironment analysis, and immune therapy response evaluation.ResultsClustering analysis of the 452 CRC patient-expressed SS-DEGs identified two subtypes: SS-like CRC (SL-CRC) and non-SS-like CRC (NSL-CRC). There were no significant differences in overall survival between the CRC subtypes. However, the subtypes displayed significant differences in immune score, stromal score, and ESTIMATE score. Based on immune therapy databases, there were also significant differences in responses to anti-CTLA-4 and anti-PD-1 immune checkpoint inhibitors between the subtypes.ConclusionOur study reveals significant differences in the immune microenvironment and immune therapy responses between SL-CRC and NSL-CRC subtypes. These findings provide a foundation for identifying new therapeutic targets and developing personalized treatment strategies for specific CRC subtypes.

Radial Data Visualization-Based Step-by-Step Eliminative Algorithm to Predict Colorectal Cancer Patients’ Response to FOLFOX Therapy

Application of the FOLFOX scheme to colorectal cancer (CRC) patients often results in the development of chemo-resistance, leading to therapy failure. This study aimed to develop a functional and easy-to-use algorithm to predict patients’ response to FOLFOX treatment. Transcriptomic data of CRC patient’s samples treated with FOLFOX were downloaded from the Gene Expression Omnibus database (GSE83129, GSE28702, GSE69657, GSE19860 and GSE41568). Comparing the expression of top up- and downregulated genes in FOLFOX responder and non-responder patients’ groups, we selected 30 potential markers that were used to create a step-by-step eliminative procedure based on modified radial data visualization, which depicts the interplay between the expression level of chosen attributes (genes) to locate data points in low-dimensional space. Our analysis proved that FOLFOX-resistant CRC samples are predominantly characterized by upregulated expression levels of TMEM182 and MCM9 and downregulated LRRFIP1. Additionally, the procedure developed based on expression levels of TMEM182, MCM9, LRRFIP1, LAMP1, FAM161A, KLHL36, ETV5, RNF168, SRSF11, NCKAP5, CRTAP, VAMP2, ZBTB49 and RIMBP2 proved to be capable in predicting FOLFOX therapy response. In conclusion, our approach can give a unique insight into clinical decision-making regarding therapy scheme administration, potentially increasing patients’ survival and, consequently, medical futility due to incorrect therapy application.

A Comparative Study of Methyl-BEAMing and Droplet Digital PCR for MGMT Gene Promoter Hypermethylation Detection

Background: O-6-methylguanine-DNA methyltransferase is responsible for the direct repair of O6-methylguanine lesions induced by alkylating agents, including temozolomide. O-6-methylguanine-DNA methyltransferase promoter hypermethylation is a well-established biomarker for temozolomide response in glioblastoma patients, also correlated with therapeutic response in colorectal cancer. Objectives: The ARETHUSA clinical trial aims to stratify colorectal cancer patients based on their mismatch repair status. Mismatch repair-deficient patients are eligible for treatment with immune checkpoint inhibitors (anti-PDL-1), whereas mismatch repair-proficient samples are screened for O-6-methylguanine-DNA methyltransferase promoter methylation to identify those suitable for temozolomide treatment. Methods: In this context, a subset of ARETHUSA metastatic colorectal cancer samples was used to compare two different techniques for assessing O-6-methylguanine-DNA methyltransferase hypermethylation: Methyl-BEAMing, a highly sensitive digital PCR approach that combines emulsion PCR and flow cytometry, and droplet digital PCR, a more automated procedure that enables the rapid, operator-independent analysis of a large number of samples. Results: Our study clearly demonstrates that the results obtained using Methyl-BEAMing and droplet digital PCR are comparable, with both techniques showing similar accuracy, sensitivity, and reproducibility. Conclusions: Digital droplet PCR proved to be an efficient method for detecting gene promoter methylation. However, the Methyl-BEAMing method has proved more sensitive for detecting low quantities of DNA.

CD248 cleaved form in human colorectal cancer stroma: implications for tumor behavior and prognosis.

CD248 (Endosialin/TEM-1) is upregulated in cancer, including colorectal cancer (CRC), but its exact role in tumor progression remains to be elucidated. Previous studies have shown that the extracellular domain of CD248 mediates the interaction between tumor cells and extracellular matrix proteins and that interfering with this interaction may reduce tumor invasion and migration activities. We have examined the expression of CD248 in 117 human CRC samples by immunohistochemistry and investigated the association with various clinicopathological features, including the occurrence of metastasis intra-tumoral immune cell density, and overall survival. Out of the 117 specimens analyzed, 76.1% (89/117) exhibited CD248-high stromal expression, while 23.1% (28/117) demonstrated CD248-low stromal expression. Interestingly, we detected the presence of a cleaved form of CD248, which appears to accumulate in the stromal extracellular matrix. A higher metastasis rate (lymph node and distant) was observed in the CD248-low group (21/28, 75.0% versus 44/89, 49.4%, p=0.02). In addition, CD248-low tumors had fewer CD163-positive macrophages and FoxP3-positive regulatory T cells (p<0.05) with no significant difference in CD8-positive T-cell infiltration and PD-L1 expression between the groups (p>0.05). Finally, overall survival was lower in CD248-low tumors than in CD248-high tumors, with 5-year survival rates of 35.7% and 57.3%, respectively (p=0.01). In a multivariate analysis, the hazard ratio of CD248-low tumors versus CD248-high tumors was 1.93 (95% confidence interval: 1.09 - 3.40; p=0.02). Our findings suggest that CD248 stromal expression may influence the TME, impacting tumor behavior and prognosis, and can serve as a promising prognostic biomarker in CRC.

SIRT2 deacetylates and decreases the expression of FOXM1 in colon cancer.

New FOXM1-specific inhibitors with the potential to be used for therapeutic purposes are under extensive research. We hypothesized that deacetylation of FOXM1 would decrease protein expression, thus providing novel therapeutic management of colon cancers. Immunostaining was used to determine FOXM1 and SIRT2 expressions in human colon cancer tissue microarrays (n = 90) from Stage I to Stage IV. SIRT2-FOXM1 interaction was evaluated in colon cancer cells using immunoprecipitation. Deacetylation of FOXM1 via SIRT2 was determined using in vitro deacetylation assays. FOXM1 could be hyper-acetylated when p300 and pCAF histone acetyltransferases were administered alongside deacetylase inhibitors. We detected that SIRT2 and FOXM1 physically interacted, and SIRT2 deacetylated FOXM1 in vitro. SIRT2 overexpression led to a significant decrease while knockdown of SIRT2 increased the FOXM1 expression in HCT116 human colon carcinoma cells. In the analysis of 90 human colorectal cancer samples, high SIRT2 expression was observed in about 49% of colorectal cancer, intermediate in 29%, and low or no staining in 22%. Strong SIRT2 expression was found to be negatively associated with the FOXM1 staining in our clinical cohort. This study reveals a molecular interaction and association between SIRT2 and FOXM1 expression in colon cancer cell lines and human colon cancer samples, and suggests that targeting SIRT2 activity using small molecule modulators may be a promising therapeutic approach for colorectal cancer.

Programmable DNA-based nanostructure sensors for mutation detection coupled with asymmetric amplification in precision genome profiling

We introduce a DNA-based nanostructure sensor for the rapid, precise identification of single-nucleotide polymorphisms (SNPs), a key factor in determining disease susceptibility and tailoring medical treatment. The proposed two-state sensor design facilitates multiplexed, sequence-specific detection of double-stranded genomic DNA (gDNA), overcoming traditional obstacles presented by base pairing interference. Utilizing detector strands with binding penalties, the sensor achieves high SNP specificity, discernible by distinct gel electrophoresis band positions. Coupled with asymmetric PCR (asy-PCR), our integrated system amplifies genetic profiling effectiveness, especially in clinical biopsies, enhancing gDNA detection sensitivity and specificity for concurrent multiple mutation identifications. This cost-effective method ($0.41 per test) streamlines mutation screening, enabling high-throughput analysis with limited equipment—requiring only a single staining agent and a unified electrophoresis apparatus. Validated clinically with 70 colorectal cancer samples, the system boasts a 98.57% sensitivity and 95.71% specificity for KRAS mutations, surpassing traditional PCR detection and uncovering low-frequency mutations untraceable by direct sequencing. Our findings suggest this asy-PCR enhanced DNA-based nanostructure sensor system has the potential to revolutionize genetic diagnostics, offering expansive applications in detecting viral variants and microbial strains, thus advancing personalized genetic testing.

CircLPHN3 correlates with prognosis in colorectal cancer and regulates cellular processes by targeting miR-142-5p.

Colorectal cancer (CRC) is often diagnosed late and has a poor prognosis. Circular RNAs (circRNAs) have been identified as prognostic biomarkers in various cancers, including CRC. The objective was to elucidate the role of circLPHN3 (hsa_circ_0069865) in CRC progression and to provide a promising prognostic marker for CRC. CircLPHN3 was identified through bioinformatics analysis of the GSE121842 dataset. The levels of circLPHN3 in CRC samples were analyzed by real time-quantitative polymerase chain reaction. Its clinical significance was assessed using the Kaplan-Meier curve and multivariate Cox regression. Downstream microRNAs of circLPHN3 were predicted with the RNAhybrid, Circular RNA Interactome, and starBase online databases. The target of miR-142-5p was predicted using miRDB, TargetScanHuman, starBase, and miRWalk databases. The relationship between circLPHN3, miR-142-5p, and LDB2 was verified by dual luciferase reporter assay. The function of circLPHN3 on CRC cell growth and metastasis was measured using Transwell and the cell counting kit-8 assay. Significant downregulation of circLPHN3 was found in CRC. CircLPHN3 was closely related to higher tumor node metastasis stage, lymph node metastasis, and predicted unfavorable prognosis. miR-142-5p was highly expressed in CRC and its expression was negatively regulated by circLPHN3. Overexpression of circLPHN3 curbed CRC cell growth, migration, and invasion, mediated by miR-142-5p. Moreover, LDB2 was identified as a target of miR-142-5p. CircLPHN3 acted as a prognostic biomarker and tumor suppressor for CRC via modulating miR-142-5p.

Robust prediction of colorectal cancer via gut microbiome 16S rRNA sequencing data.

Introduction. The study addresses the challenge of utilizing human gut microbiome data for the early detection of colorectal cancer (CRC). The research emphasizes the potential of using machine learning techniques to analyze complex microbiome datasets, providing a non-invasive approach to identifying CRC-related microbial markers.Hypothesis/Gap Statement. The primary hypothesis is that a robust machine learning-based analysis of 16S rRNA microbiome data can identify specific microbial features that serve as effective biomarkers for CRC detection, overcoming the limitations of classical statistical models in high-dimensional settings.Aim. The primary objective of this study is to explore and validate the potential of the human microbiome, specifically in the colon, as a valuable source of biomarkers for colorectal cancer (CRC) detection and progression. The focus is on developing a classifier that effectively predicts the presence of CRC and normal samples based on the analysis of three previously published faecal 16S rRNA sequencing datasets.Methodology. To achieve the aim, various machine learning techniques are employed, including random forest (RF), recursive feature elimination (RFE) and a robust correlation-based technique known as the fuzzy forest (FF). The study utilizes these methods to analyse the three datasets, comparing their performance in predicting CRC and normal samples. The emphasis is on identifying the most relevant microbial features (taxa) associated with CRC development via partial dependence plots, i.e. a machine learning tool focused on explainability, visualizing how a feature influences the predicted outcome.Results. The analysis of the three faecal 16S rRNA sequencing datasets reveals the consistent and superior predictive performance of the FF compared to the RF and RFE. Notably, FF proves effective in addressing the correlation problem when assessing the importance of microbial taxa in explaining the development of CRC. The results highlight the potential of the human microbiome as a non-invasive means to detect CRC and underscore the significance of employing FF for improved predictive accuracy.Conclusion. In conclusion, this study underscores the limitations of classical statistical techniques in handling high-dimensional information such as human microbiome data. The research demonstrates the potential of the human microbiome, specifically in the colon, as a valuable source of biomarkers for CRC detection. Applying machine learning techniques, particularly the FF, is a promising approach for building a classifier to predict CRC and normal samples. The findings advocate for integrating FF to overcome the challenges associated with correlation when identifying crucial microbial features linked to CRC development.

Multidimensional analysis of the impact of Gemmatimonas, Rhodothermus, and Sutterella on drug and treatment response in colorectal cancer.

Colorectal cancer is the third most prevalent cancer across the globe. Despite a diversity of treatment methods, the recurrence and mortality rates of the disease remain high. Recent studies have revealed a close association of the gut microbiota with the occurrence, development, treatment response, and prognosis of colorectal cancer. This study aims to integrate transcriptome and microbiome data to identify colorectal cancer subtypes associated with different gut microbiota and evaluate their roles in patient survival prognosis, tumor microenvironment (TME), and drug treatment response. An integrated analysis of microbiome data was conducted on samples of colorectal cancer from public databases. Based on this, two tumor subtypes (C1 and C2) closely associated with patient survival prognosis were identified and a risk score model was constructed. The survival status, clinical parameters, immune scores, and other features were analyzed in-depth, and the sensitivity of various potential drugs was examined. A thorough examination of microbiome information obtained from colorectal cancer patients led to the identification of two primary tumor clusters (C1 and C2), exhibiting notable variations in survival outcomes. Patients with the C1 subtype were closely associated with better prognosis, while those with the C2 subtype had higher gut microbial richness and poorer survival prognosis. A predictive model utilizing the microbiome data was developed to accurately forecast the survival outcome of patients with colorectal cancer. The TME scores provided a biological basis for risk assessment in high-risk (similar to the C2 subtype) patient cohorts. Evaluation of the sensitivity of different subtypes to various potential drugs, indicated the critical importance of personalized treatment. Further analysis showed good potential of the developed risk-scoring model in predicting immune checkpoint functions and treatment response of patients, which may be crucial in guiding the selection of immunotherapy strategies for patients with colorectal cancer. This study, through a comprehensive analysis of colorectal cancer microbiome, immune microenvironment, and drug sensitivity, enhances the current understanding of the multidimensional interactions of colorectal cancer and provides important clinical indications for improving future treatment strategies. The findings offer a new perspective on improving treatment response and long-term prognosis of patients with CRC through the regulation of microbiota or the utilization of biomarkers provided by it.

AMIGO2 enhances the invasive potential of colorectal cancer by inducing EMT.

In our previous studies, we identified amphoterin-inducible gene and open reading frame 2 (AMIGO2) as a driver gene for liver metastasis and found that AMIGO2 expression in cancer cells worsens the prognosis of patients with colorectal cancer (CRC). Epithelial-mesenchymal transition (EMT) is a trigger for CRC to acquire a malignant phenotype, such as invasive potential, leading to metastasis. However, the role of AMIGO2 expression in the invasive potential of CRC cells remains unclear. Thus, this study aimed to examine AMIGO2 expression and elucidate the mechanisms by which it induces EMT and promotes CRC invasion. Activation of the TGFβ/Smad signaling pathway was found involved in AMIGO2-induced EMT, and treatment with the TGFβ receptor inhibitor LY2109761 suppressed AMIGO2-induced EMT. Studies using CRC samples showed that AMIGO2 expression was highly upregulated in the invasive front, where AMIGO2 expression was localized to the nucleus and associated with EMT marker expression. These results suggest that the nuclear translocation of AMIGO2 induces EMT to promote CRC invasion by activating the TGFβ/Smad signaling pathway. Thus, AMIGO2 is an attractive therapeutic target for inhibiting EMT and metastatic CRC progression.

PLXNB1/SEMA4D signals mediate interactions between malignant epithelial and immune cells to promote colorectal cancer liver metastasis.

Distal metastases result from metastatic microenvironment and tumour epithelial cell interactions, the cellular heterogeneity of primary colorectal cancer (CRC) and liver metastases (LM) was evaluated by integrating single-cell sequencing data, and the collected gene expression data from metastatic epithelial cell subsets was used to construct a prognostic model and to identify intercellular receptor-ligand interactions between epithelial and immune cells in CRC and LM. Multiplex immunofluorescence staining, and invitro wound healing, cell migration and cell apoptosis assays were performed to further explore the biological relevance of identified potential regulatory molecules. In this study, approximately 17 epithelial cell subtypes were detected, with Epi-11 cells being highly expressed in LM tissues compared with CRC samples. Furthermore, patients with high expression of the metastasis-related genetic profile of Epi-11 had a poorer prognosis. By predicting receptor-ligand interactions, Epi-11 cells were found to interact more with myeloid and T/natural killer cells in LM tissues when compared to primary CRC samples, which was mediated by the PLXNB1/SEMA4D axis. In addition, high SEMA4D expression was correlated with decreased overall survival of patients with CRC, whereas PLXNB1 was not. SEMA4D knockdown prevented the migration and promoted the apoptosis of HCT116 cells invitro. In summary, Epi-11 cells, an important subset of epithelial cells, may drive the LM of CRC and act by crosstalk with immune cells through the PLXNB1/SEMA4D signalling axis.

Associations of KRAS Mutations and Clinical Characteristics of Colorectal Cancer Patients in Indonesia.

Colorectal cancer (CRC) remains a major burden worldwide, ranking third and second in incidence and mortality respectively. Detection of biomarkers including KRAS mutations can help predict prognosis and response to therapy in CRC, thus this study evaluated the frequency of KRAS mutations among Indonesian patients and their associations with clinicopathologic characteristics. Fifty-three CRC samples were collected from January to September 2022 in the Department of Surgery, Dr. Hasan Sadikin General Hospital, Bandung, Indonesia. KRAS mutations were analyzed using PCR followed by Sanger sequencing. Associations between KRAS mutations were evaluated using binary logistic regression analysis. KRAS mutations were detected in 52.8% of patients (n=28), of which 3.6% were p.Gly12Ser (n=1), 32.1% were p.Gly12Asp (n=9), 7.1% were p.Gly13Asp (n=2), 3.6% were p.Gln61His (n=1), 3.6% were p.Asp126His (n=1), and 3.6% were p.Lys169Glu (n=1). The p.Asp73= polymorphism was detected in 57.1% of the samples (n=16). KRAS mutation status did not differ significantly between the groups based on the age of onset, sex, tumor location, tumor histology, stage, and family history. KRAS mutations are present in high frequency in this cohort of CRC patients in a tertiary hospital in West Java, Indonesia. However, KRAS mutation status is not associated with the age of onset, sex, tumor location, tumor histology, stage, and family history.

Predictive nomogram of the clinical outcomes of colorectal cancer based on methylated SEPT9 and intratumoral IL-10+ Tregs infiltration

BackgroundGene methylation and the immune-related tumor microenvironment (TME) are highly correlated in tumor progression and therapeutic efficacy. Although both of them can be used to predict the clinical outcomes of colorectal cancer (CRC) patients, their predictive value is still unsatisfactory. Whether a combination risk model comprising these two prediction parameters performs better predictive effectiveness than independent factor is still unclear. Methylated Septin9 (mSEPT9) is an early diagnosis biomarker of CRC, in this study, we aimed to investigate mSEPT9-related biomarkers of immunosuppressive TME and identify the value of the combination risk model in predicting the clinical outcomes of CRC.MethodsImmunofluorescence staining was performed to clarify the correlation between intratumoral IL-10+ Treg infiltration and mSEPT9 in peripheral blood. Survival time, response to 5-fluorouracil (5-FU)-based chemotherapy and PD-1 blockade, and the probability of recurrence or metastasis were analyzed in study (197 CRC samples) and validation (195 CRC samples) sets to evaluate the efficacy of combination risk model. Potential mechanisms were explored by mRNA sequencing.ResultsHypermethylated SEPT9 in the peripheral blood of patients with CRC (stage I-III, and stage IV with resectable M1) before radical resection was positively correlated with high intratumoral IL-10+ Treg infiltration. The high-risk model revealed poor overall survival and progression-free survival, inferior therapeutic response to 5-FU-based chemotherapy and PD-1 blockade, and high probability of recurrence or metastasis. The underlying mechanisms may be associated with the increase in mSEPT9 and mediation of IL-10 via methionine metabolic reprogramming-induced infiltration of IL-10+ Tregs in the TME, which promotes tumor progression and resistance to 5-FU-based chemotherapy and PD-1 blockade.ConclusionsThe combination risk model of peripheral mSETP9 and intratumoral IL-10+ Treg infiltration in CRC can effectively predict prognosis, responsiveness to 5-FU-based chemotherapy and PD-1 blockade, and the probability of recurrence or metastasis. Therefore, this model can be used for precision treatment of CRC.

SOX17 expression in tumor endothelial cells in colorectal cancer and its association with favorable outcomes in patients

The high mortality rate of colorectal cancer (CRC) highlights the need for new treatment strategies; however, the venous invasion mechanisms in tumor endothelial cells within CRC remain unexplored. Therefore, we investigated the clinicopathological features of SRY-box transcription factor 17 (SOX17) in CRC. Immunohistochemical staining was performed on 55 CRC tissue specimens using a SOX17-specific antibody, followed by Kaplan–Meier and Cox proportional hazards regression analyses. SOX17 immunoreactivity was detected in the endothelial cells of tumor-penetrating vessels in 35/55 CRC samples. Kaplan–Meier analysis indicated that patients with SOX17 immunoreactivity had favorable overall and progression-free survival (log-rank test, P = 0.03 and 0.02, respectively). Notably, tumor endothelial SOX17 immunoreactivity was associated with a favorable prognosis in patients with stage III or IV disease (OS, P = 0.0089; PFS, P = 0.0065). Cox proportional hazard regression analysis indicated that SOX17 immunoreactivity is an independent factor for predicting favorable overall and progression-free survival in CRC (P = 0.02 and 0.01, respectively). The present findings suggest that SOX17 expression in tumor endothelial cells is a potential indicator of favorable prognosis in patients with CRC.

Identification of miR-20a as a Diagnostic and Prognostic Biomarker in Colorectal Cancer: MicroRNA Sequencing and Machine Learning Analysis.

The differential expression of miRNAs, a key regulator in many cell signaling pathways, has been studied in various malignancies and may have an important role in cancer progression, including colorectal cancer (CRC). The present study used machine learning and gene interaction study tools to explore the prognostic and diagnostic value of miRNAs in CRC. Integrative analysis of 353 CRC samples and normal tissue data was obtained from the TCGA database and further analyzed by R packages to define the deferentially expressed miRNAs (DEMs). Furthermore, machine learning and Kaplan Meier survival analysis helped better specify the significant prognostic value of miRNAs. A combination of online databases was then used to evaluate the interactions between target genes, their molecular pathways, and the correlation between the DEMs. The results indicated that miR-19b and miR-20a have a significant prognostic role and are associated with CRC progression. The ROC curve analysis discovered that miR-20a alone and combined with other miRNAs, including hsa-mir-21 and hsa-mir-542, are diagnostic biomarkers in CRC. In addition, 12 genes, including NTRK2, CDC42, EGFR, AGO2, PRKCA, HSP90AA1, TLR4, IGF1, ESR1, SMAD2, SMAD4, and NEDD4L, were found to be the highest score targets for these miRNAs. Pathway analysis identified the two correlated tyrosine kinase and MAPK signaling pathways with the key interaction genes, i.e., EGFR, CDC42, and HSP90AA1. To better define the role of these miRNAs, the ceRNA network, including lncRNAs, was also prepared. In conclusion, the combination of R data analysis and machine learning provides a robust approach to resolving complicated interactions between miRNAs and their targets.

Overexpression of Osteopontin-a and Osteopontin-c Splice Variants Are Worse Prognostic Features in Colorectal Cancer

Background: Osteopontin (OPN) is a glycoprotein involved in various physiological and pathological processes, and its aberrant expression in cancer cells is closely linked to tumor progression. In colorectal cancer (CRC), OPN is overexpressed, but the roles of its splice variants (OPN-SVs), OPNa, OPNb, and OPNc, are not well understood. This study aimed to characterize the expression patterns of OPN-SVs and their potential diagnostic and prognostic implications in CRC using transcriptomic data deposited in TSVdb and TCGA. Methods: The expression patterns of each OPN-SV were analyzed using transcriptomic data deposited in TSVdb and TCGA, which were correlated to patient data available at cBioPortal. Results: Bioinformatic analysis revealed that OPNa, OPNb, and OPNc are overexpressed in CRC samples compared to non-tumor samples. Notably, OPNa and OPNc are overexpressed in CRC stages (II, III, and IV) compared to stage I. Higher levels of OPNa and OPNc transcripts are associated with worse overall survival (OS) and shorter progression-free survival (PFS) in CRC patients. Additionally, the expression of OPNa, OPNb, and OPNc is correlated with BRAFV600E mutations in CRC samples. Conclusions: These findings suggest that OPNa and OPNc, in particular, have potential as diagnostic and prognostic biomarkers, paving the way for their further evaluation in CRC diagnosis and prognosis.

Be bold, start cold! cold formalin fixation of colorectal cancer specimens granted superior DNA and RNA quality for downstream molecular analysis

The use of cold formalin fixation (CFF; i.e., fixating tissue samples with 4 °C precooled formalin) recently attracted further attention owing to its putative improved ability to preserve nucleic acid compared with standard room temperature formalin (SFF). In this study, we aimed to assess the effect of four formalin-based fixation protocols (SFF, CFF, delayed formalin fixation-DFF, and cold formalin hyperfixation; CFH) on both DNA and RNA quality. We collected 97 colorectal cancer (CRC) and analyzed 23 metrics of nucleic acid quantity and quality yield using a multiplatform approach by combining spectrophotometric, fluorimetric, electrophoretic, and polymerase chain reaction (PCR) assays. Following confirmation of fixation-protocol-related different effects via clustering analysis, CFF presented best metrics compared with all protocols, specifically positive coefficients of DV1000-60000, DV2/DV1, DNA λ ratio 260/230, and ABL gene expression absolute copies, and negative coefficient of DV150-1000. The SFF subgroup presented a positive coefficient of DV150-1000 and negative coefficients for DV1000-60000, DV2/DV1, RNA λ ratio 260/230, RNA QuBit concentration, DV100/200, RNA electrophoresis concentration and absolute quantity, and ABL copies. Overall, we confirmed the superior yield performances of CFF preservation for both DNA and RNA compared with the other protocols in our series of CRC samples. Pending further validations and clarification of the specific mechanisms behind these findings, our study supports the implementation of CFF in the pathology unit routine specimen management for tumor tissue molecular profiling.

Exploring the Role of Escherichia coli K-12 in Reducing MIR17HG Expression as a Poor Prognostic Biomarker in Colorectal Cancer

Background: Long noncoding RNAs (lncRNAs) play significant roles in various cellular processes, and alterations in their expression levels can contribute to the pathogenesis of colorectal cancer (CRC). Objectives: This study aims to identify lncRNAs highly associated with poor prognosis in CRC and determine those that exhibit significant expression changes under the influence of Escherichia coli K-12. Methods: Potentially susceptible lncRNAs to expression modulation in the presence of E. coli K-12 were identified by analyzing GSE50040 datasets. Data from the cancer genome Atlas (TCGA) were utilized to assess E. coli K-12-affected lncRNAs with the most significant impact on CRC pathogenesis. The association between the candidate lncRNA and patient prognosis was investigated using clinical data. The co-expression network was employed to identify pathways related to the identified lncRNA via the MsigDB database. To validate the in silico findings, CRC and adjacent normal samples were examined using the RT-qPCR method. Results: Cox regression analysis demonstrated that MIR17HG is a strong biomarker associated with poor prognosis in CRC patients. Increased expression of MIR17HG in cancer samples was correlated with key pathways involving cell proliferation, anti-apoptosis, and metastasis. RT-qPCR results showed that the expression level of MIR17HG in CRC samples was significantly higher than in normal samples. Further analysis revealed that MIR17HG expression is susceptible to suppression by E. coli K-12. Conclusions: High expression of MIR17HG in cancer samples is associated with an increased probability of mortality in CRC patients. Our study highlights the potential of E. coli K-12 to reduce CRC malignancy by downregulating MIR17HG expression.

Abstract C106: Enhanced characterization of molecular attributes through multi-omics analysis and comprehensive evaluation of global and local genomic ancestry in colorectal cancer among Hispanic-Latinos

Abstract Introduction: Colorectal cancer (CRC) remains a significant public health challenge, representing the second leading cause of cancer-related mortality in the United States. Although mortality rates have generally decreased, the Hispanic/Latino (H/L) population in the Los Angeles area still experiences mortality rates up to 20% higher than those of their Caucasian American counterparts. Additionally, they are often diagnosed at a younger age and with more advanced disease stages, highlighting significant disparities in CRC outcomes. Currently, there are limited studies integrating clinical and multi-omics data from H/L populations, which are crucial for understanding the implications of colorectal tumorigenesis and addressing these disparities effectively. Methods: Clinical and genomic sequencing data were obtained from 60 primary CRC Tumor/Normal (T/N) samples within the Hispanic/Latino (H/L) population in the Los Angeles area through the PE-CGS network. For comparison, we analyzed 3,578 samples from non-Hispanic Whites (NHW) obtained from public databases. Additionally, we retrieved three CRC samples with spatial transcriptomic (ST) data from the 10xGenomics database. Using Whole Exome and RNA sequencing data, we performed somatic mutations, somatic copy number alterations (SCNAs), differential gene expression, cellular pathways, gene fusions, and global &amp; local genomic ancestry analyses. The ST data underwent analysis utilizing newly released bioinformatics tools. Clinical and genomic data were integrated. Results: In these studies, distinct Amerindian (AMR) genomic ancestry proportion, age at diagnosis, and tumor localization patterns were observed, alongside significant mutations in key genes such as APC, TP53, and KRAS. The studies revealed evident cancer heterogeneity, influenced by factors such as mutation type, microsatellite instability, tumor subsite, and ethnicity. Additionally, several previously well-defined SCNAs were detected in the majority of tumors. Comparative analysis of gene expression and cellular pathways between H/L and NHW samples revealed distinct patterns. Furthermore, we identified gene fusions that potentially contribute to oncogenic activity in CRC. Ancestry analysis pointed to a predominant AMR ancestry. Notably, distinct associations of genetic ancestry with CRC tumor clinicopathological characteristics were identified. ST analysis delineated separate cancer, immune, and stroma components within the tumors. Conclusion: Our research has explored the molecular profiling of CRC tumors in H/L patients, providing crucial insights into the characterization of CRC tumors at the DNA and RNA levels, as well as the complex clinical and genomic diversity within our target population. Additionally, it offers valuable insights into the heterogeneity of CRC tumors and the tumor microenvironment. These findings establish the groundwork for subsequent projects, potentially leading to precision medicine approaches. Citation Format: Enrique I. Velazquez-Villarreal, Brigette Waldrup, Yonatan Amzaleg, Yuxin Jin, Mackenzie Postel, Donna Loza, Serina Ovalle, Elizabeth Quino, Carmen Chavez, Julie Culver, Mariana C. Stern, Heinz-Josef Lenz, David W. Craig, John D. Carpten. Enhanced characterization of molecular attributes through multi-omics analysis and comprehensive evaluation of global and local genomic ancestry in colorectal cancer among Hispanic-Latinos [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C106.

Abstract C103: Exploring ethnicity-specific molecular mechanism of cholesterol and fatty acid synthesis pathway in Hispanic colorectal cancer

Abstract Colorectal cancer (CRC) is the most prevalent gastrointestinal cancer, the third most common malignancy and the second leading cause of cancer-related mortality worldwide. The American Cancer Society (ACS) estimates 152,810 new cases of colorectal cancer, with an estimated 53,010 deaths in 2024. Typically diagnosed in older adults, CRC incidence is rising among younger individuals, particularly in Hispanics (16.5%) compared to non-Hispanic whites (8.7%). Due to the lack of timely screenings in this ethnic group, further research is crucial to identify novel biomarkers and therapeutic targets for improved early detection and intervention. To accomplish this goal, we performed RNA-sequencing of Hispanic and non-Hispanic White (NHW) CRC tissues. The transcriptomic analysis revealed differential gene expression patterns in Hispanic and NHW populations when compared to respective normal adjacent tissues (NATs). We identified 3577 differentially expressed genes (DEGs) in Hispanic CRC samples and 2971 DEGs in NHW CRC samples, of which 1831 DEGs were unique to Hispanic. Based on the preliminary analysis we hypothesized that unique DEGs from the Hispanic population could help identify potential pathways contributing to CRC progression. Among these 1831 unique DEGs, many of the genes are associated with cholesterol and fatty acid synthesis pathway. The cholesterol biosynthesis pathway is a highly diverse and interconnected signaling pathway, playing essential roles in cellular function and systemic homeostasis. Its complexity and regulatory mechanisms make it a critical area of study in cancer. Studies indicate that Hispanics and African Americans with high cholesterol tend to have higher Body mass index (BMI) levels compared to Whites which has an increased risk of colorectal cancer. However, the role of cholesterol metabolism and fatty acid metabolism in CRC have not been studied from the Hispanic health disparities perspective. From the 1831 DEGs, we selected those in the cholesterol and fatty acid synthesis pathways with significant log2 fold changes (≤ -2 or ≥ +2) and adjusted p-values (FDR ≤ 0.05). Our bioinformatics analysis identified four key DEGs: LCN2, DHCR7, PCSK9 and SQLE. The expression levels of these genes were examined in Hispanic CRC vs. NHW CRC tissue samples using qRT-PCR. Elevated expression of LCN2 and SQLE was observed in late-stage Hispanic CRC tissues compared to NHW CRC tissues, while DHCR7 exhibited high expression in early-stage Hispanic CRC. On the other hand, PCSK9 showed low expression in both early and late stages of Hispanic CRC, suggesting potential ethnicity-specific molecular signatures in CRC progression. Moving forward, protein level studies and functional analysis of these DEGs in Hispanic CRC tissues and organoids will enhance our understanding of the role of cholesterol and fatty acid synthesis pathway proteins. Thus, elucidating novel molecular mechanisms underlying CRC progression could lead to identification of potential Hispanic specific biomarkers and therapeutic targets for early diagnosis and intervention. Citation Format: Somrita Roy, Soumya Nair, MD Zahirul Islam Khan, Sourav Roy. Exploring ethnicity-specific molecular mechanism of cholesterol and fatty acid synthesis pathway in Hispanic colorectal cancer [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C103.