Improving the overall survival prognosis prediction accuracy: A 9-gene signature in CRC patients

Novel biomarkers to predict treatment response and prognosis in locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy

PURPOSE

To identify genes associated with treatment response and prognosis for locally advanced rectal cancer (LARC) patients receiving neoadjuvant chemoradiotherapy (NCRT).

METHODS

In our cohort, gene expression profiles of 64 tumor biopsy samples before NCRT were examined and generated. Weighted gene co-expression network analysis was performed to identify gene modules. External validation datasets included GSE3493, GSE119409, and GSE133057. The expression of candidate genes was evaluated using immunohistochemistry (IHC). TIMER was used to assess immune infiltration.

RESULTS

We identified and validated the capability to predict the treatment response of CCT5 and ELF1 using our data and external validation datasets. The trends of survival differences of candidate genes in the GSE133057 dataset were similar to our cohort. High levels of CCT5 and ELF1 expression were associated with NCRT resistance and poor prognosis. Furthermore, the expression of CCT5 and ELF1 were also assessed in 117 LARC patients' samples by the IHC method. Based on IHC results and Cox analysis, the risk score model with CCT5 and ELF1 was constructed and performed well. The risk score was an independent prognostic factor for progression-free survival and overall survival in LARC patients and was then used to build nomogram models. The underlying mechanisms of CCT5 and ELF1 were explored using gene set enrichment analysis. The underlying pathway including apoptosis, cell cycle, and other processes. CCT5 and ELF1 expressions were significantly correlated with immune cell infiltration.

CONCLUSION

CCT5 and ELF1 were determined as biomarkers for treatment response and prognosis in LARC patients. The risk score model and nomograms helped predict treatment response and survival outcomes for LARC patients undergoing NCRT.

MCM5 is an oncogene of colon adenocarcinoma and promotes progression through cell cycle control

Many patients with colon adenocarcinoma (COAD) are diagnosed at an advanced stage, and the molecular mechanism of COAD progression is intricate and controversial. Therefore, there is an urgent need to identify more novel prognosis biomarkers for COAD and elucidate the molecular mechanism of this disease. The present study aimed to screen out key genes correlated with COAD prognosis. In this study, a key module was identified and four hub genes (MCM5 (encoding minichromosome maintenance complex component 5), NOLC1 (encoding nucleolar and coiled-body phosphoprotein 1), MYC (encoding MYC proto-oncogene, BHLH transcription factor), and CDK4 (encoding cyclin dependent kinase 4)) were selected that correlated with COAD prognosis, based on the GSE9348 dataset in Gene Expression Omnibus database. Gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that MCM5 correlated with the cell cycle. Furthermore, MCM5 expression was upregulated in tumor tissues of patients with COAD compared with that in adjacent tissues, based on various databases, including The Cancer Genome Atlas, the Clinical Proteomic Tumor Analysis Consortium database, and the Human Protein Atlas database. Small interfering RNA-mediated knockdown of MCM5 inhibited the cell cycle and migration of colorectal cancer cells in vitro. And western blotting results indicated that factors correlated with cell cycle (CDK2/6, Cyclin D3, P21) were downregulated after knockdown of MCM5 in vitro. Besides, downregulation of MCM5 was demonstrated to inhibit lung metastasis of COAD in nude mice model. In conclusion, MCM5 is an oncogene of COAD that promotes COAD progression via cell cycle control.

Inhibition of MORC2 Mediates HDAC4 to Promote Cellular Senescence through p53/p21 Signaling Axis

(1) Background: Colorectal cancer (CRC) is a common gastrointestinal malignancy, accounting for the second largest gastrointestinal tumor. MORC2, a newly discovered chromatin remodeling protein, plays an important role in the biological processes of various cancers. However, the potential mechanistic role of MORC2 in promoting proliferation of CRC carcinoma remains unclear. (2) Methods: The Cancer Genome Atlas database was analyzed using bioinformatics to obtain gene expression and clinical prognosis data. The cell proliferation was assessed by CCK8 and EdU assays, as well as xenograft. SA-beta-gal staining, Western blot, and ELISA assay were using to assess the cell senescence and potential mechanism. (3) Results: Our data showed that MORC2 expression was elevated in CRC patients. Depletion of MORC2 inhibited cellular proliferation both in vivo and in vitro. Further studies showed that the depletion of MORC2 enhanced p21 and p53 expression through decreasing HDAC4 and increasing pro-inflammatory factors IL-6 and IL-8, thus, promoting cellular senescence. (4) Conclusions: We concluded that increased MORC2 expression in CRC might play a critical role in tumorigenesis by regulating the cellular senescence, in addition, MORC2 could be a novel biomarker for clinical outcomes and prognosis and a treatment target for CRC.

Alternative polyadenylation associated with prognosis and therapy in colorectal cancer

Colorectal cancer (CRC) is among the most widely spread cancers globally. Aberrant alternative polyadenylation (APA) plays a role in cancer onset and its progression. Consequently, this study focused on highlighting the role of APA events and signals in the prognosis of patients with CRC. The APA events, RNA sequencing (RNA-seq), somatic mutations, copy number variants (CNVs), and clinical information of the CRC cohort were obtained from The Cancer Genome Atlas (TCGA) database and UCSC (University of California-Santa Cruz) Xena database. The whole set was sorted into two sets: a training set and a test set in a ratio of 7:3. 197 prognosis-related APA events were collected by performing univariate Cox regression signature in patients with CRC. Subsequently, a signature for APA events was established by least absolute shrinkage and selection operator (LASSO) and multivariate Cox analysis. The risk scores were measured for individual patients on the basis of the signature and patients were sorted into two groups; the high-risk group and the low-risk group as per their median risk scores. Kaplan–Meier curves, principal component analysis (PCA), and time-dependent receiver operator characteristic (ROC) curves revealed that the signature was able to predict patient prognosis effectively and further validation was provided in the test set and the whole set. The high-risk and low-risk groups displayed various distributions of mutations and CNVs. Tumor mutation burden (TMB) alone and in combination with the signature predicted the prognosis of CRC patients, but the gene frequencies of TMBs and CNVs did not change in the low- and high-risk groups. Moreover, immunotherapy and chemotherapy treatments showed different responses to PD-1 inhibitors and multiple chemotherapeutic agents in the low and high-risk groups based on the tumor immune dysfunction and exclusion (TIDE) and genomics of drugs sensitivity in cancer (GDSC) databases. This study may help in understanding the potential roles of APA in CRC, and the signature for prognosis-related APA events can work as a potential predictor for survival and treatment in patients with CRC.

SALL Proteins; Common and Antagonistic Roles in Cancer

Simple Summary

Transcription factors play essential roles in regulating gene expression, impacting the cell phenotype and function, and in the response of cells to environmental conditions. Alterations in transcription factors, including gene amplification or deletion, point mutations, and expression changes, are implicated in carcinogenesis, cancer progression, metastases, and resistance to cancer treatments. Not surprisingly, transcription factor activity is altered in numerous cancers, representing a unique class of cancer drug targets. This review updates and integrates information on the SALL family of transcription factors, highlighting the synergistic and/or antagonistic functions they perform in various cancer types.

Abstract

SALL proteins are a family of four conserved C2H2 zinc finger transcription factors that play critical roles in organogenesis during embryonic development. They regulate cell proliferation, survival, migration, and stemness; consequently, they are involved in various human genetic disorders and cancer. SALL4 is a well-recognized oncogene; however, SALL1–3 play dual roles depending on the cancer context and stage of the disease. Current reviews of SALLs have focused only on SALL2 or SALL4, lacking an integrated view of the SALL family members in cancer. Here, we update the recent advances of the SALL members in tumor development, cancer progression, and therapy, highlighting the synergistic and/or antagonistic functions they perform in similar cancer contexts. We identified common regulatory mechanisms, targets, and signaling pathways in breast, brain, liver, colon, blood, and HPV-related cancers. In addition, we discuss the potential of the SALL family members as cancer biomarkers and in the cancer cells’ response to therapies. Understanding SALL proteins’ function and relationship will open new cancer biology, clinical research, and therapy perspectives.

Improving the overall survival prognosis prediction accuracy: A 9-gene signature in CRC patients

Colorectal cancer (CRC) is a malignant tumor and morbidity rates are among the highest in the world. The variation in CRC patients' prognosis prompts an urgent need for new molecular biomarkers to improve the accuracy for predicting the CRC patients' prognosis or as a complement to the traditional TNM staging for clinical practice. CRC patients' gene expression data of HTSeq‐FPKM and matching clinical information were downloaded from The Cancer Genome Atlas (TCGA) datasets. Patients were randomly divided into a training dataset and a test dataset. By univariate and multivariate Cox regression survival analyses and Lasso regression analysis, a prediction model which divided each patient into high‐or low‐risk group was constructed. The differences in survival time between the two groups were compared by the Kaplan–Meier method and the log‐rank test. The weighted gene co‐expression network analysis (WGCNA) was used to explore the relationship between all the survival‐related genes. The survival outcomes of patients whose overall survival (OS) time were significantly lower in the high‐risk group than that in the low‐risk group both in the training and test datasets. Areas under the ROC curves which termed AUC values of our 9‐gene signature achieved 0.823 in the training dataset and 0.806 in the test dataset. A nomogram was constructed for clinical practice when we combined the 9‐gene signature with TNM stage and age to evaluate the survival time of patients with CRC, and the C‐index increased from 0.739 to 0.794. In conclusion, we identified nine novel biomarkers that not only are independent prognostic indexes for CRC patients but also can serve as a good supplement to traditional clinicopathological factors to more accurately evaluate the survival of CRC patients.