A prognostic index based on an eleven gene signature to predict systemic recurrences in colorectal cancer

Single-cell deconvolution reveals high lineage- and location-dependent heterogeneity in mesenchymal multivisceral stage 4 colorectal cancer

Metastasized colorectal cancer (CRC) is associated with a poor prognosis and rapid disease progression. Besides hepatic metastasis, peritoneal carcinomatosis is the major cause of death in Union for International Cancer Control (UICC) stage IV CRC patients. Insights into differential site-specific reconstitution of tumor cells and the corresponding tumor microenvironment are still missing. Here, we analyzed the transcriptome of single cells derived from murine multivisceral CRC and delineated the intermetastatic cellular heterogeneity regarding tumor epithelium, stroma, and immune cells. Interestingly, we found an intercellular site-specific network of cancer-associated fibroblasts and tumor epithelium during peritoneal metastasis as well as an autologous feed-forward loop in cancer stem cells. We furthermore deciphered a metastatic dysfunctional adaptive immunity by a loss of B cell-dependent antigen presentation and consecutive effector T cell exhaustion. Furthermore, we demonstrated major similarities of this murine metastatic CRC model with human disease and - based on the results of our analysis - provided an auspicious site-specific immunomodulatory treatment approach for stage IV CRC by intraperitoneal checkpoint inhibition.

Information about immune cell proportions and tumor stage improves the prediction of recurrence in patients with colorectal cancer

Predicting cancer recurrence is essential to improving the clinical outcomes of patients with colorectal cancer (CRC). Although tumor stage information has been used as a guideline to predict CRC recurrence, patients with the same stage show different clinical outcomes. Therefore, there is a need to develop a method to identify additional features for CRC recurrence prediction. Here, we developed a network-integrated multiomics (NIMO) approach to select appropriate transcriptome signatures for better CRC recurrence prediction by comparing the methylation signatures of immune cells. We validated the performance of the CRC recurrence prediction based on two independent retrospective cohorts of 114 and 110 patients. Moreover, to confirm that the prediction was improved, we used both NIMO-based immune cell proportions and TNM (tumor, node, metastasis) stage data. This work demonstrates the importance of (1) using both immune cell composition and TNM stage data and (2) identifying robust immune cell marker genes to improve CRC recurrence prediction.

Mitochondrial DNA haplogroup M7: A predictor of poor prognosis for colorectal cancer patients in Chinese population

Haplogroups and single-nucleotide polymorphisms (SNP) of mitochondrial DNA (mtDNA) were associated with the prognosis of many types of cancer patients. However, whether mtDNA haplogroups contribute to clinical outcomes of colorectal cancer (CRC) in Chinese population remains to be determined. In this study, mtDNA of tissue samples from 445 CRC patients from Northwestern China was sequenced to evaluate the association between haplogroup and prognosis. The mtDNA sequencing data of 1015 CRC patients from Southern China were collected for validation. We found patients with mtDNA haplogroup M7 had a significantly higher death risk when compared with patients with other haplogroups in both Northwestern (Hazard ratio [HR] = 3.093, 95% CI = 1.768-5.411, p < 0.001) and Southern (HR = 1.607, 95% CI = 1.050-2.459, p = 0.029) China. Then, a haplogroup M7-based mtSNP classifier was selected by using LASSO Cox regression analysis. A nomogram comprising the mtSNP classifier and clinicopathological variables was developed to predict the prognosis of CRC patients (area under the curve [AUC] 0.735, 95% CI = 0.679-0.791). Furthermore, patients with high- and low-risk scores calculated by the haplogroup M7-based mtSNP classifier exhibited significantly different overall survival (OS) and recurrence-free survival (RFS) (all p < 0.001). Finally, RNA-seq and immunohistochemical analyses indicated the poor prognosis of patients with haplogroup M7 may be related to mitochondrial dysfunction and immune abnormalities in CRC tissues. In conclusion, the haplogroup M7 and haplogroup M7-based mtSNP classifier seems to be a practical and reliable prognostic predictor for CRC patients, which provides a potential tool of clinical decision-making for patients with haplogroup M7 in Chinese population.

Multi-omics analysis reveals a molecular landscape of the early recurrence and early metastasis in pan-cancer

Cancer remains a formidable challenge in medicine due to its propensity for recurrence and metastasis, which can result in unfavorable treatment outcomes. This challenge is particularly acute for early-stage patients, who may experience recurrence and metastasis without timely detection. Here, we first analyzed the differences in clinical characteristics among the primary tumor, recurrent tumor, and metastatic tumor in different stages of cancer, which may be caused by the molecular level. Moreover, the importance of predicting early cancer recurrence and metastasis is emphasized by survival analyses. Next, we used a multi-omics approach to identify key molecular changes associated with early cancer recurrence and metastasis and discovered that early metastasis in cancer demonstrated a high degree of genomic and cellular heterogeneity. We performed statistical comparisons for each level of omics data including gene expression, mutation, copy number variation, immune cell infiltration, and cell status. Then, various analytical techniques, such as proportional hazard model and Fisher's exact test, were used to identify specific genes or immune characteristics associated with early cancer recurrence and metastasis. For example, we observed that the overexpression of BPIFB1 and high initial B-cell infiltration levels are linked to early cancer recurrence, while the overexpression or amplification of ANKRD22 and LIPM, mutation of IGHA1 and MUC16, high fibroblast infiltration level, M1 polarization of macrophages, cellular status of DNA repair are all linked to early cancer metastasis. These findings have led us to construct classifiers, and the average area under the curve (AUC) of these classifiers was greater than 0.75 in The Cancer Genome Atlas (TCGA) cancer patients, confirming that the features we identified could be biomarkers for predicting recurrence and metastasis of early cancer. Finally, we identified specific early sensitive targets for targeted therapy and immune checkpoint inhibitor therapy. Once the biomarkers we identified changed, treatment-sensitive targets can be treated accordingly. Our study has comprehensively characterized the multi-omics characteristics and identified a panel of biomarkers of early cancer recurrence and metastasis. Overall, it provides a valuable resource for cancer recurrence and metastasis research and improves our understanding of the underlying mechanisms driving early cancer recurrence and metastasis.

OTOP2, Inversely Modulated by miR-3148, Inhibits CRC Cell Migration, Proliferation and Epithelial–Mesenchymal Transition: Evidence from Bioinformatics Data Mining and Experimental Verification

Introduction

Colorectal cancer (CRC) represents one of the most frequent human malignancies with its underlying pathogenesis still unclear. The prevalence of multi-omics in screening biomarkers associated with CRC has largely accelerated our understanding into the pathophysiology of CRC. The present work aimed to mine the Gene Expression Omnibus (GEO) datasets associated with CRC studies and identify potential targets correlated with CRC pathogenesis.

Methods

We screened the DEGs in GSE50760 and GSE104178 and performed functional Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Furthermore, the overlapped DEGs were subjected to functional GO enrichment and KEGG pathway enrichment analysis. The protein–protein interaction (PPI) network and miRNA-mRNA network were constructed based on the overlapped DEGs. The in vitro functional assays including qRT-PCR, caspase-3 and -9 activity assay, wound healing assay, CCK-8 assay and luciferase reporter assay were performed to determine the role of OTOP2/miR-3148 axis in regulating CRC cell progression.

Results

Fifty-three overlapped genes were screened over GSE50760 and GSE104178 and ten hub genes were identified by PPI network analysis. Expression levels of GCG, SST, NPY, GUCA2B, PYY, UCN3, GUCA2A, TMEM82 and BEST4 were not correlated with the overall survival of patients with CRC. However, the high expression of otopetrin 2 (OTOP2) in the CRC tissues was significantly correlated with better overall survival of patients with CRC. The expression of OTOP2 in CRC tissues was significantly lowever than that in normal ones. The in vitro functional assays demonstrated that OTOP2 silence reduced caspase-3/-9 activities, promoted cell migration, proliferation and epithelial–mesenchymal transition in HT29 and SW620 cells. Furthermore, miR-3148 could inversely regulate OTOP2 expression in CRC cell lines.

Conclusion

Collectively, the work suggested the potential role of the OTOP2/miR-3148 axis in the pathophysiology of CRC by mining the GEO database.

Characterization of the consensus mucosal microbiome of colorectal cancer

Dysbioisis is an imbalance of an organ's microbiome and plays a role in colorectal cancer pathogenesis. Characterizing the bacteria in the microenvironment of a cancer through genome sequencing has advantages compared to culture-based profiling. However, there are notable technical and analytical challenges in characterizing universal features of tumor microbiomes. Colorectal tumors demonstrate microbiome variation among different studies and across individual patients. To address these issues, we conducted a computational study to determine a consensus microbiome for colorectal cancer, analyzing 924 tumors from eight independent RNA-Seq data sets. A standardized meta-transcriptomic analysis pipeline was established with quality control metrics. Microbiome profiles across different cohorts were compared and recurrently altered microbial shifts specific to colorectal cancer were determined. We identified cancer-specific set of 114 microbial species associated with tumors that were found among all investigated studies. Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria were among the four most abundant phyla for the colorectal cancer microbiome. Member species of Clostridia were depleted and Fusobacterium nucleatum was one of the most enriched bacterial species in tumors. Associations between the consensus species and specific immune cell types were noted. Our results are available as a web data resource for other researchers to explore (https://crc-microbiome.stanford.edu).

Identification of an Autophagy-Related Gene Signature for the Prediction of Prognosis in Early-Stage Colorectal Cancer

Purpose: A certain number of early-stage colorectal cancer (CRC) patients suffer tumor recurrence after initial curative resection. In this context, an effective prognostic biomarker model is constantly in need. Autophagy exhibits a dual role in tumorigenesis. Our study aims to develop an autophagy-related gene (ATG) signature-based on high-throughput data analysis for disease-free survival (DFS) prognosis of patients with stage I/II CRC.

Methods: Gene expression profiles and clinical information of CRC patients extracted from four public datasets were distributed to discovery and training cohort (GSE39582), validation cohort (TCGA CRC, n = 624), and meta-validation cohort (GSE37892 and GSE14333, n = 420). Autophagy genes significantly associated with prognosis were identified.

Results: Among 655 autophagy-related genes, a 10-gene ATG signature, which was significantly associated with DFS in the training cohort (HR, 2.76[1.56–4.82]; p = 2.06 × 10–4), was constructed. The ATG signature, stratifying patients into high and low autophagy risk groups, was validated in the validation (HR, 2.29[1.15–4.55]; p = 1.5 × 10–2) and meta-validation cohorts (HR, 2.5[1.03–6.06]; p = 3.63 × 10–2) and proved to be prognostic in a multivariate analysis. Functional analysis revealed enrichment of several immune/inflammatory pathways in the high autophagy risk group, where increased infiltration of T regulatory cells (Tregs) and decreased infiltration of M1 macrophages were observed.

Conclusion: Our study established a prognostic ATG signature that effectively predicted DFS for early-stage CRC patients. Meanwhile, the study also revealed the possible relationship among autophagy process, immune/inflammatory response, and tumorigenesis.

USH2A Mutation is Associated With Tumor Mutation Burden and Antitumor Immunity in Patients With Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is one of the diseases with the highest morbidity and mortality in the world. At present, immunotherapy has become a valuable method for the treatment of COAD. Tumor mutational burden (TMB) is considered to be the most common biomarker for predicting immunotherapy. According to reports, the mutation rate of COAD ranks third. However, whether these gene mutations are related to TMB and immune response is still unknown. Here, COAD somatic mutation data were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Bioinformatics methods were used to study the relationships among gene mutations, COAD survival prognosis, and tumor immune response. A total of 22 of the top 40 mutations in TCGA and ICGC databases were the same. Among them, the USH2A mutation was associated with high TMB and poor clinical prognosis. According to Gene Set Enrichment Analysis (GSEA) and the CIBERSORT algorithm, we determined that the USH2A mutation upregulates signaling pathways involved in the immune system and the antitumor immune response. In cases with a USH2A mutation, the immune score and MSI score of TCGA samples increased, the expression of immune checkpoint genes decreased significantly, and the TIDE score decreased significantly. Dependent on the presence or absence of a USH2A mutation, TCGA COAD samples were analyzed for differentially expressed genes, 522 of which were identified. Using a univariate Cox analysis and LASSO COX analysis of these differential genes, a prediction model was established, which established significant differences in the infiltration of immune cells, immune checkpoint gene expression, immune score, MSI score, TMB, and TIDE in patients in high- and low-risk groups. In conclusion, mutation of USH2A is frequent in COAD and is related to an increase in TMB and the antitumor immunity. The differential genes screened by USH2A mutation allowed the construction of a risk model for predicting the survival and prognosis of cancer patients, in addition to providing new ideas for COAD immunotherapy.

Single-Cell Transcriptomics Reveals the Expression of Aging- and Senescence-Associated Genes in Distinct Cancer Cell Populations

The human aging process is associated with molecular changes and cellular degeneration, resulting in a significant increase in cancer incidence with age. Despite their potential correlation, the relationship between cancer- and ageing-related transcriptional changes is largely unknown. In this study, we aimed to analyze aging-associated transcriptional patterns in publicly available bulk mRNA-seq and single-cell RNA-seq (scRNA-seq) datasets for chronic myelogenous leukemia (CML), colorectal cancer (CRC), hepatocellular carcinoma (HCC), lung cancer (LC), and pancreatic ductal adenocarcinoma (PDAC). Indeed, we detected that various aging/senescence-induced genes (ASIGs) were upregulated in malignant diseases compared to healthy control samples. To elucidate the importance of ASIGs during cell development, pseudotime analyses were performed, which revealed a late enrichment of distinct cancer-specific ASIG signatures. Notably, we were able to demonstrate that all cancer entities analyzed in this study comprised cell populations expressing ASIGs. While only minor correlations were detected between ASIGs and transcriptome-wide changes in PDAC, a high proportion of ASIGs was induced in CML, CRC, HCC, and LC samples. These unique cellular subpopulations could serve as a basis for future studies on the role of aging and senescence in human malignancies.

An 11-gene signature for the prediction of systemic recurrences in colon adenocarcinoma

Background

Prognosis varies among patients within the same colon adenocarcinoma (COAD) stage, indicating the need for reliable molecular markers to enable individualized treatment. This study aimed to investigate gene signatures that can be used for better prognostic prediction of COAD.

Methods

Gene-expression profiles of COAD patients were obtained from the Gene Expression Omnibus database (n = 332) and The Cancer Genome Atlas database (n = 431). The relationship between gene signature and relapse-free survival was analysed in the training set (n = 93) and validated in the internal validation set (n = 94) and external validation sets (n = 145 and 431).

Results

Overall, 11 genes (N-myc downstream regulated gene 1 [NDRG1], fms-like tyrosine kinase 1 [FLT1], lipopolysaccharide binding protein [LBP], fatty acid binding protein 4 [FABP4], adiponectin gene [ADIPOQ], angiotensinogen gene [AGT], activin A receptor, type II-like kinase 1 [ACVRL1], CC chemokine ligand 11 [CCL11], cell division cycle 42 [CDC42], T-cell receptor alpha variable 9_2 [TRAV9_2], and proopiomelanocortin [POMC]) were identified by univariable and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Based on the risk-score model, the patients were grouped into the high-risk or low-risk groups using the median risk score as the cut-off. The area under the curve (AUC) values for 1-, 3-, and 5-year recurrence were 0.970, 0.849, and 0.859, respectively. Patients in the high-risk group had significantly poorer relapse-free survival than did those in the low-risk group. The predictive accuracy of the 11-gene signature was proven in the validation sets. Our gene signature showed better predictive performance for 1-, 3-, and 5-year recurrence than did the other four models.

Conclusions

The 11-gene signature showed good performance in predicting recurrence in COAD. The accuracy of the signature for prognostic classification requires further confirmation.

Resectable Colorectal Cancer: Current Perceptions on the Correlation of Recurrence Risk, Microbiota and Detection of Genetic Mutations in Liquid Biopsies

Metastatic colorectal cancer (mCRC) remains a highly lethal malignancy, although considerable progress has resulted from molecular alterations in guiding optimal use of available treatments. CRC recurrence remains a great barrier in the disease management. Hence, the spotlight turns to newly mapped fields concerning recurrence risk factors in patients with resectable CRC with a focus on genetic mutations, microbiota remodeling and liquid biopsies. There is an urgent need for novel biomarkers to address disease recurrence since specific genetic signatures can identify a higher or lower recurrence risk (RR) and, thus, be used both as biomarkers and treatment targets. To a large extent, CRC is mediated by the immune and inflammatory interplay of microbiota, through intestinal dysbiosis. Clarification of these mechanisms will yield new opportunities, leading not only to the appropriate stratification policies, but also to more precise, personalized monitoring and treatment navigation. Under this perspective, early detection of post-operative CRC recurrence is of utmost importance. Ongoing trials, focusing on circulating tumor cells (CTCs) and, even more, circulating tumor DNA (ctDNA), seem to pave the way to a promising, minimally invasive but accurate and life-saving monitoring, not only supporting personalized treatment but favoring patients' quality of life, as well.

Activation of TC10-Like Transcription by Lysine Demethylase KDM4B in Colorectal Cancer Cells

Malignant colorectal cancers (CRCs) are characterized by enhanced migration and invasion thus acquiring the ability to metastasize. We have previously shown that the small GTPase TC10-like (TCL) contributes to aggressive migration and invasion in malignant CRC cells. TCL expression is differentially expressed in CRC cells and can be upregulated by hypoxia although the underlying epigenetic mechanism is not fully appreciated. Here, we report that differential TCL expression in CRC cells appeared to be associated with histone H3K9 methylation. RNAi screening revealed that the lysine demethylase KDM4B was essential for TCL transcription in CRC cells. KDM4B interacted with and was recruited by the sequence-specific transcription factor ETS-related gene 1 (ERG1) to the TCL promoter to activate transcription. Mechanistically, KDM4B mediated H3K9 demethylase facilitated the assembly of pre-initiation complex (PIC) on the TCL promoter. KDM4B knockdown attenuated migration and invasion of CRC cells. Importantly, KDM4B expression was upregulated in human CRC specimens of advanced stages compared to those of lower grades and associated with poor prognosis. Together, these data uncover a novel epigenetic mechanism underlying malignant transformation of CRC cells and suggest that KDM4B may be considered as a therapeutic target in CRC intervention.

Clinical Value of Consensus Molecular Subtypes in Colorectal Cancer: A Systematic Review and Meta-Analysis

Background

The consensus molecular subtypes (CMSs) of colorectal cancer (CRC) capture tumor heterogeneity at the gene-expression level. Currently, a restricted number of molecular features are used to guide treatment for CRC. We summarize the evidence on the clinical value of the CMSs.

Methods

We systematically identified studies in Medline and Embase that evaluated the prognostic and predictive value of CMSs in CRC patients. A random-effect meta-analysis was performed on prognostic data. Predictive data were summarized.

Results

In local disease, CMS4 tumors were associated with worse overall survival (OS) compared with CMS1 (hazard ratio [HR] = 3.28, 95% confidence interval = 1.27 to 8.47) and CMS2 cancers (HR = 2.60, 95% confidence interval = 1.93 to 3.50). In metastatic disease, CMS1 consistently had worse survival than CMS2-4 (OS HR range = 0.33-0.55; progression-free survival HR range = 0.53-0.89). Adjuvant chemotherapy in stage II and III CRC was most beneficial for OS in CMS2 and CMS3 (HR range = 0.16-0.45) and not effective in CMS4 tumors. In metastatic CMS4 cancers, an irinotecan-based regimen improved outcome compared with oxaliplatin (HR range = 0.31-0.72). The addition of bevacizumab seemed beneficial in CMS1, and anti-epidermal growth factor receptor therapy improved outcome for KRAS wild-type CMS2 patients.

Conclusions

The CMS classification holds clear potential for clinical use in predicting both prognosis and response to systemic therapy, which seems to be independent of the classifier used. Prospective studies are warranted to support implementation of the CMS taxonomy in clinical practice.

Characterization of the Survival Influential Genes in Carcinogenesis

The genes influencing cancer patient mortality have been studied by survival analysis for many years. However, most studies utilized them only to support their findings associated with patient prognosis: their roles in carcinogenesis have not yet been revealed. Herein, we applied an in silico approach, integrating the Cox regression model with effect size estimated by the Monte Carlo algorithm, to screen survival-influential genes in more than 6000 tumor samples across 16 cancer types. We observed that the survival-influential genes had cancer-dependent properties. Moreover, the functional modules formed by the harmful genes were consistently associated with cell cycle in 12 out of the 16 cancer types and pan-cancer, showing that dysregulation of the cell cycle could harm patient prognosis in cancer. The functional modules formed by the protective genes are more diverse in cancers; the most prevalent functions are relevant for immune response, implying that patients with different cancer types might develop different mechanisms against carcinogenesis. We also identified a harmful set of 10 genes, with potential as prognostic biomarkers in pan-cancer. Briefly, our results demonstrated that the survival-influential genes could reveal underlying mechanisms in carcinogenesis and might provide clues for developing therapeutic targets for cancers.

Identification and Validation of a Novel Six-Gene Prognostic Signature of Stem Cell Characteristic in Colon Cancer

Cancer stem cells play crucial roles in the development of colon cancer (COAD). This study tried to explore new markers for predicting the prognosis of colon cancer based on stem cell-related genes. In our study, 424 COAD samples from TCGA were divided into three subtypes based on 412 stem cell-related genes; there were significant differences in prognosis, clinical characteristics, and immune scores between these subtypes. 694 genes were screened between subgroups. Subsequently a six-gene signature (DYDC2, MS4A15, MAGEA1, WNT7A, APOD, and SERPINE1) was established. This model had strong robustness and stable predictive performance in cohorts of different platforms. Taken together, the six-gene signature constructed in this study could be used as a novel prognostic marker for COAD patients.

Natural podophyllotoxin analog 4DPG attenuates EMT and colorectal cancer progression via activation of checkpoint kinase 2

Epithelial–mesenchymal transition (EMT) is critical for the metastatic dissemination of cancer cells and contributes to drug resistance. In this study, we observed that epithelial colorectal cancer (CRC) cells transiently exposed to 5-fluorouracil (5-FU) (a chemotherapeutic drug for CRC) as well as 5-FU-resistant cells (5-FU-R) develop EMT characters as evidenced by activation of Vimentin and augmented invasive properties. On the other hand, 4DPG (4′-demethyl-deoxypodophyllotoxin glucoside), a natural podophyllotoxin analog attenuates EMT and invadopodia formation abilities of HCT-116/5-FU-R and SW-620/5-FU-R cells. Treatment with 4DPG restrains Vimentin phosphorylation (Ser38) in 5-FU-R cells, along with downregulation of mesenchymal markers Twist1 and MMP-2 while augmenting the expression of epithelial markers E-cadherin and TIMP-1. Moreover, 4DPG boosts the tumor-suppressor protein, checkpoint kinase 2 (Chk2) via phosphorylation at Thr68 in a dose-dependent manner in 5-FU-R cells. Mechanistically, SiRNA-mediated silencing of Chk2, as well as treatment with Chk2-specific small-molecule inhibitor (PV1019), divulges that 4DPG represses Vimentin activation in a Chk2-dependent manner. Furthermore, immunoprecipitation analysis unveiled that 4DPG prevents complex formation between Vimentin and p53 resulting in the rescue of p53 and its nuclear localization in aggressive 5-FU-R cells. In addition, 4DPG confers suitable pharmacokinetic properties and strongly abrogates tumor growth, polyps formation, and lung metastasis in an orthotopic rat colorectal carcinoma model. In conclusion, our findings demonstrate 4DPG as a targeted antitumor/anti-metastatic pharmacological lead compound to circumvent EMT-associated drug resistance and suggest its clinical benefits for the treatment of aggressive cancers.

Gene Expression Along with Genomic Copy Number Variation and Mutational Analysis Were Used to Develop a 9-Gene Signature for Estimating Prognosis of COAD

PURPOSE

This study aims to systematically analyze multi-omics data to explore new prognosis biomarkers in colon adenocarcinoma (COAD).

MATERIALS AND METHODS

Multi-omics data of COAD and clinical information were obtained from The Cancer Genome Atlas (TCGA). Univariate Cox analysis was used to select genes which significantly related to the overall survival. GISTIC 2.0 software was used to identify significant amplification or deletion. Mutsig 2.0 software was used to identify significant mutation genes. The 9-gene signature was screened by random forest algorithm and Cox regression analysis. GSE17538 dataset was used as an external dataset to verify the predictive ability of 9-gene signature. qPCR was used to detect the expression of 9 genes in clinical specimens.

RESULTS

A total of 71 candidate genes are obtained by integrating genomic variation, mutation and prognostic data. Then, 9-gene signature was established, which includes HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, PYGO2, CTNNA1, PTPRK, and NAT1. The 9-gene signature is an independent prognostic risk factor for COAD patients. In addition, the signature shows good predicting performance and clinical practicality in training set, testing set and external verification set. The results of qPCR based on clinical samples showed that the expression of HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, and PYGO2 was increased in colon cancer tissues and the expression of CTNNA1, PTPRK, NAT1 was decreased in colon cancer tissues.

CONCLUSION

In this study, 9-gene signature is constructed as a new prognostic marker to predict the survival of COAD patients.

The influence of PD-L1 genetic variation on the prognosis of R0 resection colorectal cancer patients received capecitabine-based adjuvant chemotherapy: a long-term follow-up, real-world retrospective study

PURPOSE

This study investigated the influence of PD-L1 genetic variation on the prognosis of R0 resection colorectal cancer (CRC) patients who received capecitabine-based adjuvant chemotherapy in real world.

METHODS

A total of 315 CRC patients underwent R0 surgical resection and received capecitabine-based adjuvant chemotherapy were included. Clinical characteristics were collected from the hospital record system, prognosis was obtained by telephone follow-up. Peripheral blood and peripheral blood mononuclear cell (PBMC) specimen of CRC patients were performed for the genotyping of polymorphism and mRNA expression of PD-L1, respectively. Analysis on the association between genotypes and prognosis was conducted.

RESULTS

The median disease-free survival (DFS) of the 315 CRC patients was 5.1 years, the median overall survival (OS) was 6.0 years. Regarding the PD-L1 gene polymorphism analysis, the prevalence of 901T>C among the CRC patients was as follows: TT genotype 221 cases (70.16%), TC genotype 86 cases (27.30%), CC genotype 8 cases (2.54%), the minor allele frequency was 0.16, the distribution of three genotypes was in accordance with Hardy-Weinberg equilibrium (P = 0.915). Moreover, the prognosis analysis indicated that the median DFS of patients with TT and TC/CC genotype was 5.4 and 4.0 years, respectively (P = 0.008). The median OS of patients with the two genotypes was 6.4 and 5.0 years (P = 0.007). The multivariate Cox regression analysis showed that the TC/CC genotypes were an independent factor for DFS (odds ratio = 1.56, P = 0.018). Furthermore, the mRNA expression results indicated that the mRNA expression of PD-L1 in PBMC of the patients with TC/CC genotype was significantly higher than patients with TT genotype (P < 0.001).

CONCLUSION

The prognosis of R0 resection CRC patients received capecitabine-based adjuvant chemotherapy in real world may be influenced by PD-L1 901T>C polymorphism through mediation of the mRNA expression of PD-L1.