DNA Repair–Related Gene Signature in Predicting Prognosis of Colorectal Cancer Patients

Identification of a distinctive immunogenomic gene signature in stage-matched colorectal cancer

BACKGROUND

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Despite advances in diagnosis and treatment, including surgery, chemotherapy, and immunotherapy, accurate clinical markers are still lacking. The development of prognostic and predictive indicators, particularly in the context of personalized medicine, could significantly improve CRC patient management.

METHOD

In this retrospective study, we used FFPE blocks of tissue samples from CRC patients at Augusta University (AU) to quantify a custom 15-gene panel. To differentiate the tumor and adjacent normal regions (NAT), H&E staining was utilized. For the quantification of transcripts, we used the NanoString nCounter platform. Kaplan-Meier and Log-rank tests were used to perform survival analyses. Several independent datasets were explored to validate the gene signature. Orthogonal analyses included single-cell profiling, differential gene expression, immune cell deconvolution, neoantigen prediction, and biological pathway assessment.

RESULTS

A 3-gene signature (GTF3A, PKM, and VEGFA) was found to be associated with overall survival in the AU cohort (HR = 2.26, 95% CI 1.05-4.84, p = 0.02, 93 patients), TCGA cohort (HR = 1.57, 95% CI 1.05-2.35, p < 0.02, 435 patients) and four other GEO datasets. Independent single-cell analysis identified relatively higher expression of the 3-gene signature in the tumor region. Differential analysis revealed dysregulated tissue inflammation, immune dysfunction, and neoantigen load of cell cycle processes among high-risk patients compared to low-risk patients.

CONCLUSION

We developed a 3-gene signature with the potential for prognostic and predictive clinical assessment of CRC patients. This gene-based stratification offers a cost-effective approach to personalized cancer management. Further research using similar methods could identify therapy-specific gene signatures to strengthen the development of personalized medicine for CRC patients.

Incorporating Novel Technologies in Precision Oncology for Colorectal Cancer: Advancing Personalized Medicine

Colorectal cancer (CRC) is one of the most heterogeneous and deadly diseases, with a global incidence of 1.5 million cases per year. Genomics has revolutionized the clinical management of CRC by enabling comprehensive molecular profiling of cancer. However, a deeper understanding of the molecular factors is needed to identify new prognostic and predictive markers that can assist in designing more effective therapeutic regimens for the improved management of CRC. Recent breakthroughs in single-cell analysis have identified new cell subtypes that play a critical role in tumor progression and could serve as potential therapeutic targets. Spatial analysis of the transcriptome and proteome holds the key to unlocking pathogenic cellular interactions, while liquid biopsy profiling of molecular variables from serum holds great potential for monitoring therapy resistance. Furthermore, gene expression signatures from various pathways have emerged as promising prognostic indicators in colorectal cancer and have the potential to enhance the development of equitable medicine. The advancement of these technologies for identifying new markers, particularly in the domain of predictive and personalized medicine, has the potential to improve the management of patients with CRC. Further investigations utilizing similar methods could uncover molecular subtypes specific to emerging therapies, potentially strengthening the development of personalized medicine for CRC patients.

The DNA damage repair-related lncRNAs signature predicts the prognosis and immunotherapy response in gastric cancer

Background

Gastric cancer (GC) is one of the most prevalent cancers, and it has unsatisfactory overall treatment outcomes. DNA damage repair (DDR) is a complicated process for signal transduction that causes cancer. lncRNAs can influence the formation and incidence of cancers by influencing DDR-related mRNAs/miRNAs. A DDR-related lncRNA prognostic model is urgently needed to improve treatment strategies.

Methods

The data of GC samples were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. A total of 588 mRNAs involved in DDR were selected from MSigDB, 62 differentially expressed mRNAs from TCGA-STAD were obtained, and 137 lncRNAs were correlated with these mRNAs. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to develop a DDR-related lncRNA prognostic model. Based on the risk model, the differentially expressed gene signature A/B in the low-risk and high-risk groups of TCGA-STAD was identified for further validation.

Results

The prognosis model of 5 genes (AC145285.6, MAGI2-AS3, AL590705.3, AC007405.3, and LINC00106) was constructed and classified into two risk groups. We found that GC patients with a low-risk score had a better OS than those with a high-risk score. We found that the high-risk group tended to have higher TME scores. We also found that patients in the high-risk group had a higher proportion of resting CD4 T cells, monocytes, M2 macrophages, resting dendritic cells, and resting mast cells, whereas the low-risk subgroup had a greater abundance of activated CD4 T cells, follicular helper T cells, M0 macrophages, and M1 macrophages. We observed significant differences in the T-cell exclusion score, T-cell dysfunction, MSI, and TMB between the two risk groups. In addition, we found that patients treated with immunotherapy in the low-RS score group had a longer survival and a better prognosis than those in the high-RS score group.

Conclusion

The prognostic model has a significant role in the TME, clinicopathological characteristics, prognosis, MSI, and drug sensitivity. We also discovered that patients treated with immunotherapy in the low-RS score group had a better prognosis. This work provides a foundation for improving the prognosis and response to immunotherapy among patients with GC.

Integrated analysis to identify the prognostic and immunotherapeutic roles of coagulation-associated gene signature in clear cell renal cell carcinoma

The coagulation system is closely related to the physiological status and immune response of the body. Recent years, studies focusing on the association between coagulation system abnormalities and tumor progression have been widely reported. In clear cell renal cell carcinoma (ccRCC), poor prognosis often occurs in patients with venous tumor thrombosis and coagulation system abnormalities, and there is a lack of research in related fields. Significant differences in coagulation function were also demonstrated in our clinical sample of patients with high ccRCC stage or grade. Therefore, in this study, we analyzed the biological functions of coagulation-related genes (CRGs) in ccRCC patients using single-cell sequencing and TCGA data to establish the 5-CRGs based diagnostic signature and predictive signature for ccRCC. Univariate and multivariate Cox analyses suggested that prognostic signature could be an independent risk factor. Meanwhile, we applied CRGs for consistent clustering of ccRCC patients, and the two classes showed significant survival and genotype differences. The differences in individualized treatment between the two different subtypes were revealed by pathway enrichment analysis and immune cell infiltration analysis. In summary, we present the first systematic analysis of the significance of CRGs in the diagnosis, prognosis, and individualized treatment of ccRCC patients.

Prognosis and Novel Drug Targets for Key lncRNAs of Epigenetic Modification in Colorectal Cancer

Background

Colorectal cancer (CRC) has been the 3rd most commonly malignant tumor of the gastrointestinal tract in the world. 5-Methylcytosine (m⁵C) and long noncoding RNAs (lncRNAs) have an essential role in predicting the prognosis and immune response for CRC patients. Therefore, we built a m⁵C-related lncRNA (m⁵CRlncRNA) model to investigate the prognosis and treatment methods for CRC patients.

Methods

Firstly, we secured the transcriptome and clinical data for CRC from The Cancer Genome Atlas (TCGA). Then, m⁵CRlncRNAs were recognized by coexpression analysis. Then, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were utilized to build m⁵C-related prognostic characteristics. Besides, Kaplan-Meier analysis, ROC, PCA, C-index, enrichment analysis, and nomogram were performed to investigate the model. Additionally, immunotherapy responses and antitumor medicines were explored for CRC patients.

Results

A total of 8 m⁵C-related lncRNAs (AC093157.1, LINC00513, AC025171.4, AC090948.2, ZEB1-AS1, AC109449.1, AC009041.3, and LINC02516) were adopted to construct a risk model to investigate survival and prognosis for CRC patients. CRC samples were separated into low- and high-risk groups, with the latter having a worse prognosis. The m⁵C-related lncRNA model helps us to better distinguish immunotherapy responses and IC50 of antitumor medicines in different groups of CRC patients.

Conclusion

The research may give new perspectives on tailored therapy approaches as well as novel theories for forecasting the prognosis of CRC patients.

Topoisomerase IIβ binding protein 1 serves as a novel prognostic biomarker for stage II-III colorectal cancer patients

BACKGROUND

Colorectal cancer (CRC) is a commonly diagnosed human malignancy worldwide. Accumulating evidence has suggested DNA repair related proteins widely participate in CRC initiation and development. TOPBP1 is recently identified as a novel regulator for DNA repair, however, its biological role in CRC remains unknown.

METHODS

Firstly, the bioinformatics analysis was utilized to investigate the expression and clinical significance of TOPBP1 in CRC patients. Then, a retrospective study enrolling 129 stage II/III CRC patients was performed for validation. The CCK-8, colony formation, transwell assay and xenograft model were used to clarify the biological impact of TOPBP1 on CRC cells. Finally, transcriptome sequencing was performed to investigate the potential oncogenic mechanisms regulated by TOPBP1 in CRC development.

RESULTS

The expression of TOPBP1 was significantly higher in CRC tissues than that in normal tissues. High TOPBP1 expression was an independent unfavorable prognostic factor for overall and disease-free survival in II/III CRC patients. Knockdown of TOPBP1 not only significantly inhibited the proliferation, colony formation, invasion, migration and epithelial-mesenchymal transition (EMT) molecular phenotype of CRC cells, while the opposite was for TOPBP1 expression. Moreover, knockdown of TOPBP1 slowed down the growth speed of xenografts. The transcriptome sequencing identified MAP3K3 as a downstream gene of TOPBP1 and MAP3K3 knockdown inhibited the EMT molecular phenotype in CRC cells. Finally, the rescue assay indicated MAP3K3 overexpression counteracted the inhibitory effect of TOPBP1 knockdown on the proliferation, colony formation, invasion, migration and EMT phenotype of CRC cells.

CONCLUSION

TOPBP1 promotes the malignant progression of CRC through MAP3K3 induced EMT. TOPBP1 is a promising clinical biomarker or therapeutical target for CRC patients.

Is red blood cell distribution width a prognostic factor for colorectal cancer? A meta-analysis

Background

RDW might be an easy and cost-effective pre-operative prognostic factor for cancer patients. The aim of the current study was to analyze whether red blood cell distribution width (RDW) was a prognostic factor for colorectal cancer (CRC) patients who underwent radical surgery.

Methods

We conducted the searching strategy in three databases including the PubMed, Embase and Cochrane Library from the inception to May 07, 2022, to find eligible studies. In this meta-analysis, we focused on the prognosis. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for overall survival (OS), disease-free survival (DFS) and cancer-specific survival (CSS).

Results

A total of seven studies involving 7,541 patients were included in this meta-analysis. After pooling up the HRs, red blood cell distribution width-coefficient of variation (RDW-CV) was not an independent prognostic factor of OS (HR = 1.48, I²= 90%, 95% CI = 0.93 to 2.36, P = 0.10), however, red blood cell distribution width-standard deviation (RDW-SD) was an independent prognostic factor of OS (HR = 1.99, I²= 0%, 95% CI = 1.59 to 2.49, P < 0.01). As for DFS, we found that RDW-CV (HR = 1.51, I²= 83%, 95% CI = 0.94 to 2.43, P = 0.09 < 0.10) and RDW-SD (HR = 1.77, I²= 56%, 95% CI = 0.91 to 3.43, P = 0.09 < 0.10) were both the independent prognostic factors. In terms of CSS, we found that RDW-CV was not an independent prognostic factor (HR = 1.23, I²= 95%, 95% CI = 0.72 to 2.10, P = 0.46).

Conclusion

RDW-SD was an independent prognostic factor of OS and DFS, and RDW-CV was an independent prognostic factor of DFS.