Analysis of factors potentially predicting prognosis of colorectal cancer

Correlation between spleen density and prognostic outcomes in patients with colorectal cancer after curative resection

OBJECTIVE

The objective of this study was to investigate the correlation between spleen density and the prognostic outcomes of patients who underwent curative resection for colorectal cancer (CRC).

METHODS

The clinical data of patients who were diagnosed with CRC and underwent radical resection were retrospectively analyzed. Spleen density was determined using computed tomography. Analysis of spleen density in relation to overall survival (OS) and disease-free survival (DFS) utilizing the Kaplan-Meier method. Univariate and multivariate Cox regression models were used to screen for independent prognostic factors, and a nomogram was constructed to predict OS and DFS. Moreover, internally validated using a bootstrap resamplling method.

RESULTS

Two hundred twelve patients were included, of whom 23 (10.85%) were defined as having a diffuse reduction of spleen density (DROSD) based on diagnostic cutoff values (spleen density≦37.00HU). Kaplan-Meier analysis indicated that patients with DROSD had worse OS and DFS than those non-DROSD (P < 0.05). Multivariate Cox regression analysis revealed that DROSD, carbohydrate antigen 199 (CA199) > 37 U/mL, tumor node metastasis (TNM) stage III-IV, laparoscopy-assisted operation and American Society of Anesthesiology (ASA) score were independent risk factors for 3-year DFS. DROSD, CA199 > 37 U/mL, TNM stage III-IV, hypoalbuminemia, laparoscopy-assisted operation and ASA score were chosen as predictors of for 3-year OS. Nomograms showed satisfactory accuracy in predicting OS and DFS using calibration curves, decision curve analysis and bootstrap resamplling method.

CONCLUSION

Patients with DROSD who underwent curative resection have worse 3-year DFS and OS. The nomogram demonstrated good performance, particularly in predicting 3-year DFS with a net clinical benefit superior to well-established risk calculator.

Survival rate of colorectal cancer in China: A systematic review and meta-analysis

Background

This study aims to comprehensively summarize the colorectal survival rate in China. Method: In PubMed and Web of Science, keywords such as "colorectal cancer", "survival" and "China" were used to search literatures in the past 10 years. Random effect models were selected to summarize 1-year, 3-year, and 5-year survival rates, and meta-regression and subgroup analyses were performed on the included studies.

Results

A total of 16 retrospective and prospective studies providing survival rates for colorectal cancer in China were included. The 1-year, 3-year, and 5-year survival rates of colorectal cancer in China were 0.79, 0.72 and 0.62, respectively. In the included studies, the 5-year survival rates of stage I (5474 cases), stage II (9215 cases), stage III (8048 cases), and stage IV (4199 cases) colorectal cancer patients were 0.85, 0.81, 0.57 and 0.30, respectively. Among them, the 5-year survival rates of colorectal cancer were 0.82, 0.76, 0.71, 0.67, 0.66, 0.65 and 0.63 in Tianjin, Beijing, Guangdong, Shandong, Liaoning, Zhejiang and Shanghai, respectively.

Conclusion

The 5-year survival rate in China is close to that of most European countries, but still lower than Japan and South Korea, and the gap is gradually narrowing. Region, stage, differentiation, pathological type, and surgical approach can affect 5-year survival in colorectal cancer.

Systematic review registration

https://www.crd.york.ac.uk/prospero/ identifier, CRD42022357789.

Comprehensive exploration of tumor immune microenvironment feature and therapeutic response in colorectal cancer based on a novel immune-related long non-coding RNA prognostic signature

Colorectal cancer (CRC) is one of the most common malignant tumors with a high incidence rate and mortality. LncRNA is an important regulator of the immune system. It is of great significance to study immune-related lncRNAs (IR-lncRNAs) for CRC. In this study, we screened IR-lncRNAs differentially expressed in normal and CRC tissues, and Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator were applied to construct IR-lncRNA prognostic signature in TCGA training dataset, and its predictive capability for the prognosis of CRC patients was verified in GSE39582 validation dataset. The novel signature was identified as an independent predictor of prognosis in CRC patients. In addition, the signature could accurately predict the feature of the immune microenvironment and therapeutic response in CRC patients. The CMap database was adopted to screen for small molecule candidate drugs that can reverse and treat high-risk CRC patients. Finally, the expression of six IR-lncRNAs were verified by qRT-PCR in clinical specimens from our patient cohort. In conclusion, we construct an IR-lncRNA prognostic signature, which is a powerful biomarker of CRC and can accurately predict the prognosis, immune microenvironment feature, and therapeutic response of CRC patients.

Prognostic value of p16, p53, and pcna in sarcoma and an evaluation of immune infiltration

Background

p16, p53, and proliferating cell nuclear antigen (pcna) genes play significant roles in many chromatin modifications and have been found to be highly expressed in a variety of tumor tissues. Therefore, they have been used as target genes for some tumor therapies. However, the differential expressions of the p16, p53, and pcna genes in human sarcomas and their effects on prognosis have not been widely reported.

Methods

The Oncomine dataset was used to analyze the transcription levels of p16, p53, and pcna genes, and the gene expression profile interactive analysis (GEPIA) dataset was used to analyze the differential expressions of p16, p53, and pcna. The expression levels of p16, p53, and pcna were further analyzed by Western Blotting. GEPIA and Kaplan–Meier analyses were used to analyze the prognostic value of p16, p53, and pcna. Furthermore, p16, p53, and pcna gene mutations and their association with overall survival (OS) and disease-free survival (DFS) were analyzed using cBioPortal datasets. In addition, genes co-expressed with p16, p53, and pcna were analyzed using Oncomine. The DAVID dataset was used to analyze the functional enrichment of p16, p53, pcna, and their co-expressed genes by Gene Ontology (GO) and Metascape were used to construct a network map. Finally, the immune cell infiltration of p16, p53, and pcna in patients with sarcoma was reported by Tumor Immune Estimation Resource (TIMER).

Results

p16, p53, and pcna were up-regulated in human sarcoma tissues and almost all sarcoma cell lines. Western Blotting showed that the expression of p16, p53, and pcna was elevated in osteosarcoma cell lines. The expression of pcna was correlated with OS, the expression of p16, p53, and pcna was correlated with relapse-free survival, and the genetic mutation of p16 was negatively correlated with OS and DFS. We also found that p16, p53, and pcna genes were positively/negatively correlated with immune cell infiltration in sarcoma.

Conclusions

The results of this study showed that p16, p53, and pcna can significantly affect the survival and immune status of sarcoma patients. Therefore, p16, p53, and pcna could be used as potential biomarkers of prognosis and immune infiltration in human sarcoma and provide a possible therapeutic target for sarcoma.

The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases

The recent advances in gene chip technology have led to the identification of multiple metabolism-related genes that are closely associated with colorectal cancer (CRC). Nevertheless, none of these genes could accurately diagnose or predict CRC. The prognosis of CRC has been made by previous prognostic models constructed by using multiple genes, however, the predictive function of multi-gene prognostic models using metabolic genes for the CRC prognosis remains unexplored. In this study, we used the TCGA-CRC cohort as the test dataset and the GSE39582 cohort as the experimental dataset. Firstly, we constructed a prognostic model using metabolic genes from the TCGA-CRC cohort, which were also associated with CRC prognosis. We analyzed the advantages of the prognostic model in the prognosis of CRC and its regulatory mechanism of the genes associated with the model. Secondly, the outcome of the TCGA-CRC cohort analysis was validated using the GSE39582 cohort. We found that the prognostic model can be employed as an independent prognostic risk factor for estimating the CRC survival rate. Besides, compared with traditional clinical pathology, it can precisely predict CRC prognosis as well. The high-risk group of the prognostic model showed a substantially lower survival rate as compared to the low-risk group. In addition, gene enrichment analysis of metabolic genes showed that genes in the prognostic model are enriched in metabolism and cancer-related pathways, which may explain its underlying mechanism. Our study identified a novel metabolic profile containing 11 genes for prognostic prediction of CRC. The prognostic model may unravel the imbalanced metabolic microenvironment, and it might promote the development of biomarkers for predicting treatment response and streamlining metabolic therapy in CRC.

Lead Time and Prognostic Role of Serum CEA, CA19-9, IL-6, CRP, and YKL-40 after Adjuvant Chemotherapy in Colorectal Cancer

In colorectal cancer (CRC), 20-50% of patients relapse after curative-intent surgery with or without adjuvant therapy. We investigated the lead times and prognostic value of post-adjuvant (8 months from randomisation to adjuvant treatment) serum CEA, CA19-9, IL-6, CRP, and YKL-40. We included 147 radically resected stage II-IV CRC treated with 24 weeks of adjuvant 5-fluorouracil-based chemotherapy in the phase III LIPSYT-study (ISRCTN98405441). All 147 were included in lead time analysis, but 12 relapsing during adjuvant therapy were excluded from post-adjuvant analysis. Elevated post-adjuvant CEA, IL-6, and CRP were associated with impaired disease-free survival (DFS) with hazard ratio (HR) 5.21 (95% confidence interval 2.32-11.69); 3.72 (1.99-6.95); 2.58 (1.18-5.61), respectively, and elevated IL-6 and CRP with impaired overall survival (OS) HR 3.06 (1.64-5.73); 3.41 (1.55-7.49), respectively. Elevated post-adjuvant IL-6 in CEA-normal patients identified a subgroup with impaired DFS. HR 3.12 (1.38-7.04) and OS, HR 3.20 (1.39-7.37). The lead times between the elevated biomarker and radiological relapse were 7.8 months for CEA and 10.0-53.1 months for CA19-9, IL-6, CRP, and YKL-40, and the lead time for the five combined was 27.3 months. Elevated post-adjuvant CEA, IL-6, and CRP were associated with impaired DFS. The lead time was shortest for CEA.

The Prognostic Value of New Index (LANR) Composed of Pre-operative Lymphocytes, Albumin, and Neutrophils in Patients With Resectable Colorectal Cancer

Background: Inflammatory factors and nutritional status are critical to the prognosis of colorectal cancer patients. This study aimed to investigate the prognostic value of the combination of preoperative lymphocytes, albumin, and neutrophils (LANR) in patients with resectable colorectal cancer.

Methods: A total of 753 patients with pathologically diagnosed primary colorectal cancer were included in the study. The value of LANR was defined as follows: LANR, lymphocyte × albumin/neutrophil. The ROC curve, subgroup analysis and Cox proportional hazard regression analysis were used to assess the prognostic value of LANR in overall survival and progression-free survival.

Results: The median age of the patients was 60 years (range 52–67 years). In overall survival, the area under the curve of LANR was 0.6276, and the HR (95% CI) was 0.551 (0.393–0.772). And in progression-free survival, the area under the curve of LANR was 0.5963, and the HR (95% CI) was 0.697 (0.550–0.884). The results indicate that preoperative LANR may be a reliable predictor of overall and progression-free survival in resectable colorectal cancer patients.

Conclusions: LANR is an important prognostic indicator for patients with resectable colorectal cancer, and it can also provide a reference for clinicians and patients to choose a treatment plan.