Plasma Protein Profiling Reveal Osteoprotegerin as a Marker of Prognostic Impact for Colorectal Cancer

Preoperative Immunocite-Derived Ratios Predict Surgical Complications Better when Artificial Neural Networks Are Used for Analysis-A Pilot Comparative Study

We aimed to comparatively assess the prognostic preoperative value of the main peripheral blood components and their ratios-the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR)-to the use of artificial-neural-network analysis in determining undesired postoperative outcomes in colorectal cancer patients. Our retrospective study included 281 patients undergoing elective radical surgery for colorectal cancer in the last seven years. The preoperative values of SII, NLR, LMR, and PLR were analyzed in relation to postoperative complications, with a special emphasis on their ability to accurately predict the occurrence of anastomotic leak. A feed-forward fully connected multilayer perceptron network (MLP) was trained and tested alongside conventional statistical tools to assess the predictive value of the abovementioned blood markers in terms of sensitivity and specificity. Statistically significant differences and moderate correlation levels were observed for SII and NLR in predicting the anastomotic leak rate and degree of postoperative complications. No correlations were found between the LMR and PLR or the abovementioned outcomes. The MLP network analysis showed superior prediction value in terms of both sensitivity (0.78 ± 0.07; 0.74 ± 0.04; 0.71 ± 0.13) and specificity (0.81 ± 0.11; 0.69 ± 0.03; 0.9 ± 0.04) for all the given tasks. Preoperative SII and NLR appear to be modest prognostic factors for anastomotic leakage and overall morbidity. Using an artificial neural network offers superior prognostic results in the preoperative risk assessment for overall morbidity and anastomotic leak rate.

TNFRSF11B Suppresses Memory CD4+ T Cell Infiltration in the Colon Cancer Microenvironment: A Multiomics Integrative Analysis

Background

Colorectal cancer is a lethal cancer worldwide. Due to the low tumor mutation burden and low proportion of tumor-infiltrating lymphocytes in the microenvironment of most patients, innovative immunotherapeutic approaches need to be identified.

Methods

Using the TCGA-COAD dataset (n = 514), we identified TNFRSF11B as a prognostic factor of colon cancer. An immunohistochemistry (IHC) dataset (n = 86), 290 single colorectal cancer cells (GSE81861), and 31 paired colon cancer transcriptional datasets were further applied to validate the function of TNFRSF11B, which was confirmed via fluorescence-activated cell sorting (FACS) analysis.

Results

A risk score system consisting of eight immune-related genes (IRGs) (FGFR2, ZC3HAV1L, TNFRSF11B, CD79A, IGHV3-11, IGHV3-21, IGKV2D-30, and IGKV6D-21) was constructed to predict the prognosis of colon cancer patients. Only TNFRSF11B was closely correlated with late-stage lymph node metastasis and worse survival outcomes (p = 0.010, p = 0.014, and p = 0.0061). In our IHC dataset, 72.09% (62/86) of the colon cancer patients had TNFRSF11B overexpression with significantly shorter overall survival times (p = 0.072). High TNFRSF11B expression typically had a later TNM stage (p = 0.067), a higher frequency of lymph node (p = 0.029) and lymphovascular (p = 0.007) invasion, and a higher incidence of pneumonia (p = 0.056) than their counterparts. The expression of six genes (KRT18, ARPC5L, ACTG1, ARPC2, EZR, and YWHAZ) related to pathogenic E. coli infection was simultaneously increased with TNFRSF11B overexpression via gene set enrichment analysis (GSEA). These genes are involved in the regulation of the actin cytoskeleton, shigellosis, bacterial invasion of epithelial cells, and Salmonella infection. Finally, only activated memory CD4⁺ T cells (p = 0.017) were significantly decreased in the high TNFRSF11B expression group via CIBERSORT comparison, which was confirmed by TIMER2.0 analysis of the TCGA-COAD dataset. We also performed FACS analysis to show that TNFRSF11B decreased the infiltration of central memory CD4⁺ T cells and effector memory CD4⁺ T cells in the colorectal cancer microenvironment (all p <0.001).

Conclusion

TNFRSF11B acts as a prognostic factor for colon cancer patients and could affect the colon cancer immune response. TNFRSF11B was closely related to lymph node invasion and pathogenic E. coli. infection, which may negatively affect memory-activated CD4+ T cell infiltration in colon cancer.

Plasma Prokineticin 1, a prognostic biomarker in colorectal cancer patients with curative resection: a retrospective cohort study

BACKGROUND

Prokineticin 1 (PROK1) was reported as an angiogenic factor, which is associated with tumor progression, cell invasion, and metastasis in colorectal cancer. Although the association between PROK1 expression in primary cancer lesion and patient prognosis was reported, it is unclear whether plasma PROK1 concentration may be a predictive factor in colorectal cancer patients. This study investigated the association between PROK1 concentration in plasma and prognosis in colorectal cancer patients.

METHODS

We measured preoperative PROK1 plasma levels using ELISA method, while PROK1 expression in primary cancer lesion was evaluated using immunohistochemistry (IHC). The association between plasma PROK1 levels and cancer-related survival rate (CRS) was evaluated. Additionally, we examined whether simultaneous PROK1 expression in both primary cancer lesions and plasma was correlated with CRS. The cancer-related survival rate was calculated using the Kaplan-Meier method, and survival estimates were compared using the log-rank test.

RESULTS

We have gathered eligible 130 CRC patients retrospectively. Out of 130 patients, 61 (46.9%) were positive on IHC in primary cancer, and 69 (53.1%) were negative, while 43 (33.1%) had high-value PROK1 in plasma. Out of these 43, 30 (25.4%) also had concomitant higher IHC expression in primary cancer. The plasma PROK1 levels tended to increase with advancing stages. The plasma PROK1-positive group had a lower 5-year CRS than the negative group (63.6% vs. 88.2%; P = 0.006). Additionally, simultaneous PROK1 expression was associated with a more significant decrease of 5-year CRS than both negative groups in all stages (76.2% vs. 92.5%; P = 0.003) and stage III (59.3% vs. 84.5%; P = 0.047). Multivariate analysis showed simultaneous PROK1 expression was independently associated with worse CRS (HR, 1.97; 95% CI 1.20‑3.24, P < 0.01).

CONCLUSION

PROK1 expression in preoperative plasma reflects poor prognosis in patients undergoing curative resection for colorectal cancer. The plasma PROK1 level may be a potential predictive marker, especially in stage III colorectal cancer patients.

Predictive values profiling of interleukin-2, interleukin-8, tumor necrosis factor-α, procalcitonin, and C-reactive protein in critical gastrointestinal cancer patients

Background

The prognostic values of serum cytokines in cancer have not yet been fully determined. The objective of this study was to identify potential biomarkers associated with clinical outcomes in critical gastrointestinal (GI) cancer patients.

Methods

A retrospective analysis was performed to quantify serum interleukin (IL)-2, IL-8, tumor necrosis factor-α (TNF-α), procalcitonin (PCT), and C-reactive protein (CRP) for correlation with clinical outcomes in GI cancer patients. The patients were divided into tertiles or quartiles based on the cytokine levels: Q1, Q2, and Q3, or Q1, Q2, Q3, and Q4. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values of the cytokines.

Results

Trend analysis showed that IL-2, IL-8, TNF-α, PCT, and CRP levels had significant positive correlations with mortality in GI cancer patients (all P-values were lower than 0.05). The significance was observed in Q3 vs. Q1 in IL-2 (P=0.026), Q3 vs. Q1 in IL-8 (P=0.003), Q2 and Q3 vs. Q1 in TNF-α (P=0.012 and P=0.002, respectively), Q4 vs. Q1 in PCT (P=0.031), Q3 and Q4 vs. Q1 in CRP (P=0.011 and P=0.001, respectively). The area under curve (AUC) of IL-2, IL-8, TNF-α, PCT, and CRP were 0.706, 0.729, 0.743, 0.769, and 0.736, and the optimal cutoff points were determined at 838 U/mL, 46.15 pg/mL, 11.95 pg/mL, 0.77 pg/mL, and 109.38 mg/L, respectively. Under these critical values, the sensitivity was 73.3%, 66.7%, 80.0%, 93.3%, and 86.7%, and the specificity was 64.9%, 72.0%, 60.4%, 61.8%, and 68.9%, respectively.

Conclusions

In GI cancer patients, serum IL-2, IL-8, TNF-α, PCT, and CRP levels can provide potential prognostic values for predicting clinical outcomes. The results may facilitate the exploration of cancer-related cytokine networks and development of novel therapy for GI cancer patients.

Plasma protein biomarkers for early detection of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, mainly due to late diagnosis at advanced tumor stages. In this study, we aimed to identify plasma protein biomarkers for early detection of PDAC. Totally, 135 PDAC patients (early PDAC, Stage I/II, n = 71; advanced PDAC, Stage III/IV, n = 64), 13 benign lesions/chronic pancreatitis patients and 72 healthy individuals, with corresponding plasma samples from a case-control study in Sweden were included. A proximity extension assay was used to detect 92 cancer-related proteins, and an enzyme-linked immunosorbent assay/electrochemiluminescence immunoassay was used to detect CA19-9. Predictive features were selected from these 93 candidate proteins and three covariates in the Swedish participants, and then validated in Spanish participants, including 37 early PDAC patients, 38 advanced PDAC patients, 19 chronic pancreatitis patients and 36 healthy controls. A panel of eight proteins discriminating early PDAC from healthy individuals was identified, and the cross-validated area under the curves (AUCs) were 0.85 (95% confidence interval, 95% CI, 0.78-0.91) and 0.81 (95% CI, 0.70-0.92) in the Swedish and Spanish participants, respectively. Another eight-protein panel was predictive for classifying advanced PDAC from healthy controls in two populations, with cross-validated AUCs of 0.89 (95% CI, 0.83-0.95) and 0.90 (95% CI, 0.83-0.98), respectively. In conclusion, eight protein biomarkers were identified and externally validated, potentially allowing early detection of PDAC patients if validated in additional prospective studies.

Colorectal Cancer and Bone Tissue: Fantastic Relations and Where to Find Them

Colorectal cancer (CRC) is the third most common cancer worldwide. There is a need for the early diagnosis of CRC for a better prognostic outcome. It is, therefore, crucial to understand the CRC pathogenesis in all its aspects. In many cases, one of the main causes of cancer-related deaths is the presence of metastases. In this context, an often overlooked aspect is the metastatic tropism, since CRC, like other cancers, is more prone to metastasize some organs rather than others. Beyond the liver and lung, and differently from other types of cancers, a not usual site of CRC metastases is the bone. However, it may assume a crucial role in the development and the outcome of the disease. Therefore, this review aims to discuss the complex relations between bone markers and CRC pathogenesis, suggesting the use of these molecules as potential targets for therapeutic purposes. Different osteogenic molecules, some of whom are growth factors and are implicated in the different osteogenic pathways, have been proved to also be involved in CRC progression. Some of them are oncogenes, while others oncosuppressors, and in a future perspective, some of them may represent new potential CRC biomarkers.

Systemic inflammation in colorectal cancer: Underlying factors, effects, and prognostic significance

Systemic inflammation is a marker of poor prognosis preoperatively present in around 20%-40% of colorectal cancer patients. The hallmarks of systemic inflammation include an increased production of proinflammatory cytokines and acute phase proteins that enter the circulation. While the low-level systemic inflammation is often clinically silent, its consequences are many and may ultimately lead to chronic cancer-associated wasting, cachexia. In this review, we discuss the pathogenesis of cancer-related systemic inflammation, explore the role of systemic inflammation in promoting cancer growth, escaping antitumor defense, and shifting metabolic pathways, and how these changes are related to less favorable outcome.