Peripheral monocyte counts predict the clinical outcome for patients with colorectal cancer: a systematic review and meta-analysis

Causal impacts of 731 immunocyte phenotypes on colorectal cancer-evidence from a bidirectional two-sample Mendelian randomization

Colorectal cancer is one of the most common and lethal malignancies, and various factors have been confirmed to contribute to its occurrence. However, the causal role of immune cell-specific changes in the development of colorectal cancer has not been investigated. The bidirectional two-sample Mendelian randomization analysis was performed to explore the association between 731 types of immune cell phenotypes-specific changes and colorectal cancer. The inverse variance weighting results indicated that a total of 31 and 28 immune cell phenotypes significantly associated with colorectal cancer in two different datasets, respectively. The primary results of inverse variance weighting Mendelian randomization suggested that the immune cell phenotypes BAFF-R on IgD+ CD38dim (OR = 1.033, 95%CI: 1.005-1.062) and SSC-A on monocyte (OR = 1.055, 95%CI: 1.016-1.096) served as risk factor for colorectal cancer. In addition, the meta-analysis further supports the causal link of BAFF-R on IgD+ CD38dim (pooled OR = 1.035, 95%CI: 1.013-1.059) and SSC-A on monocyte (pooled OR = 1.060, 95%CI: 1.026-1.095) with colorectal cancer. Finally, the inverse variance weighting Mendelian randomization result suggested that genetic determinants of colorectal cancer may decrease the level of HLA DR++ monocyte absolute count (OR = 0.686, 95%CI: 0.508-0.925). Our results indicated that the potential causal association of BAFF-R on IgD+ CD38dim and SSC-A on monocyte with colorectal cancer. The identified immune cells may be appealing drug targets for colorectal cancer, but lack confirmation from real clinical evidence. Further studies are needed to investigate the roles of these immune cells in colorectal cancer.

CD16+ as predictive marker for early relapse in aggressive B-NHL/DLBCL patients

Assessing the prognosis of patients with aggressive non-Hodgkin B cell lymphoma mainly relies on a clinical risk score (IPI). Standard first-line therapies are based on a chemo-immunotherapy with rituximab, which mediates CD16-dependent antibody-dependent cellular cytotoxicity (ADCC). We phenotypically and functionally analyzed blood samples from 46 patients focusing on CD16+ NK cells, CD16+ T cells and CD16+ monocytes. Kaplan-Meier survival curves show a superior progression-free survival (PFS) for patients having more than 1.6% CD16+ T cells (p = 0.02; HR = 0.13 (0.007-0.67)) but an inferior PFS having more than 10.0% CD16+ monocytes (p = 0.0003; HR = 16.0 (3.1-291.9)) at diagnosis. Surprisingly, no correlation with NK cells was found. The increased risk of relapse in the presence of > 10.0% CD16+ monocytes is reversed by the simultaneous occurrence of > 1.6% CD16+ T cells. The unexpectedly strong protective function of CD16+ T cells could be explained by their high antibody-dependent cellular cytotoxicity as quantified by real-time killing assays and single-cell imaging. The combined analysis of CD16+ monocytes (> 10%) and CD16+ T cells (< 1.6%) provided a strong model with a Harrell's C index of 0.80 and a very strong power of 0.996 even with our sample size of 46 patients. CD16 assessment in the initial blood analysis is thus a precise marker for early relapse prediction.

Phenotypic and functional heterogeneity of monocytes in health and cancer in the era of high dimensional technologies

Monocytes have been traditionally classified in three discrete subsets, which can participate in the immune responses as effector cells or as precursors of myeloid-derived cells in circulation and tissues. However, recent advances in single-cell omics have revealed unprecedented phenotypic and functional heterogeneity that goes well beyond the three conventional monocytic subsets and propose a more fluid differentiation model. This novel concept does not only apply to the monocytes in circulation but also at the tissue site. Consequently, the binary model proposed for differentiating monocyte into M1 and M2 macrophages has been recently challenged by a spectrum model that more realistically mirrors the heterogeneous cues in inflammatory conditions. This review describes the latest results on the high dimensional characterization of monocytes and monocyte-derived myeloid cells in steady state and cancer. We discuss how environmental cues and monocyte-intrinsic properties may affect their differentiation toward specific functional and phenotypic subsets, the causes of monocyte expansion and reduction in cancer, their metabolic requirements, and the potential effect on tumor immunity.

Prognostic significance of preoperative prognostic immune and nutritional index in patients with stage I-III colorectal cancer

BACKGROUND

To explore the value of preoperative prognostic immune and nutritional index (PINI) in predicting postoperative complications and long-term outcomes in patients with stage I-III colorectal cancer (CRC).

METHODS

Restricted cubic splines were used to assess the relationship between PINI and survival in patients with CRC. The Kaplan-Meier method and log-rank test were used to plot the survival curves. The Cox proportional hazards model was used to evaluate independent prognostic predictors in patients with CRC. A logistic regression analysis was performed to identify independent predictors of postoperative complications. The least absolute shrinkage and selection operator (LASSO) logistic regression algorithm was used for feature screening.

RESULTS

An evident positive dose-response relationship between PINI and survival in patients with CRC was identified. Compared with patients with a high PINI, those with a low PINI had worse disease-free survival (DFS) (47.9% vs. 66.9%, p < 0.001) and overall survival (OS) (49.7% vs. 70.2%, p < 0.001). The Cox proportional hazards model revealed that PINI was independently associated with DFS (hazard ratio [HR], 0.823; 95% confidence interval [CI], 0.754-0.898; p < 0.001) and OS (HR, 0.833; 95% CI, 0.761-0.912; p < 0.001) in patients with CRC. In the logistic regression analysis, PINI was an independent factor affecting postoperative complications in patients with CRC (odds ratio, 0.710; 95%CI: 0.610-0.810, p < 0.001). The LASSO logistic regression algorithm was used to screen for effective prognostic variables. Finally, we constructed PINI-based nomograms to predict postoperative 1-5-year PFS, and OS in patients with CRC.

CONCLUSION

PINI is an effective biomarker for predicting postoperative complications, DFS, and OS in patients with stage I-III CRC.

Value Research of NLR, PLR, and RDW in Prognostic Assessment of Patients with Colorectal Cancer

Objective

This study aimed to investigate the relevance of the study with the neutrophil count and lymphocyte count ratio (NLR), platelet count and lymphocyte count ratio (PLR), and red blood cell distribution width (RDW) in the prognostic evaluation of colorectal cancer patients.

Methods

143 patients with colorectal cancer from January 2016 to January 2019 were selected by our hospital, and then, other 143 cases of physical examiners as normal groups were selecting to proceed colonoscopic biopsy to diagnose 106 cases of precancerous diseases related to colorectal cancer. Among them were the inflammatory bowel group (n = 56) and the colorectal polyp group (n = 50). Analysis of the survival impact factors of patients with carcinoma of the rectum, preoperative NLR, ROW, PLR, and prognostic relationship, and comparison of NLR, PLR, and RDW diagnostic rate and expression were performed.

Results

Tissue type, TNM stage, lymph node metastasis, NLR, RDW, and PLR had a predictive influence on patients with colorectal cancer (P0.05). There was no link between gender, age, aetiology, pathological type, and prognosis in patients with colorectal cancer (P > 0.05). Multiple variables in patients with colorectal cancer are affected by tissue categorization (poor differentiation), TNM stages (III, IV), lymph node metastases, NLR, ROW, and PLR (P0.05). When compared to solo NLR, Row, and PLR diagnostics, the combination diagnosis and malignancy rates were greater, and the differences were statistically significant (P0.05). Diagnostic sensitivity, specificity, and accuracy were greater when compared to single NLR, ROW, and PLR. When compared to the normal control group, NLR, ROW, and PLR have greater levels, and the differences are statistically significant (P0.05). The patient survival declines more slowly as PLR, NLR, and the severity of the condition rises.

Conclusion

NLR, ROW, and PLR combined diagnosis has high accuracy in colorectal cancer diagnosis, and the prognosis of patients with NLR, ROW, and PLR levels has a tight association; so, clinically, the above signs should be identified, and the optimal treatment time is grasped.

Bioinformatics analysis reveals immune prognostic markers for overall survival of colorectal cancer patients: a novel machine learning survival predictive system

Objectives

Immune microenvironment was closely related to the occurrence and progression of colorectal cancer (CRC). The objective of the current research was to develop and verify a Machine learning survival predictive system for CRC based on immune gene expression data and machine learning algorithms.

Methods

The current study performed differentially expressed analyses between normal tissues and tumor tissues. Univariate Cox regression was used to screen prognostic markers for CRC. Prognostic immune genes and transcription factors were used to construct an immune-related regulatory network. Three machine learning algorithms were used to create an Machine learning survival predictive system for CRC. Concordance indexes, calibration curves, and Brier scores were used to evaluate the performance of prognostic model.

Results

Twenty immune genes (BCL2L12, FKBP10, XKRX, WFS1, TESC, CCR7, SPACA3, LY6G6C, L1CAM, OSM, EXTL1, LY6D, FCRL5, MYEOV, FOXD1, REG3G, HAPLN1, MAOB, TNFSF11, and AMIGO3) were recognized as independent risk factors for CRC. A prognostic nomogram was developed based on the previous immune genes. Concordance indexes were 0.852, 0.778, and 0.818 for 1-, 3- and 5-year survival. This prognostic model could discriminate high risk patients with poor prognosis from low risk patients with favorable prognosis.

Conclusions

The current study identified twenty prognostic immune genes for CRC patients and constructed an immune-related regulatory network. Based on three machine learning algorithms, the current research provided three individual mortality predictive curves. The Machine learning survival predictive system was available at: https://zhangzhiqiao8.shinyapps.io/Artificial_Intelligence_Survival_Prediction_for_CRC_B1005_1/, which was valuable for individualized treatment decision before surgery.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04657-3.

The pharmacokinetics of PEGylated liposomal doxorubicin are not significantly affected by sex in rats or humans, but may be affected by immune dysfunction

PEGylated liposomal doxorubicin (PLD, Caelyx®, Doxil®) has been suggested to show significant sex-based differences in plasma clearance, as well as high inter-individual variability that may be driven by monocyte counts in cancer patients. This study aimed to establish if these differences are similarly observed in rats, which exhibit similar liposome clearance mechanisms to humans, and to use this model to identify sources of inter-individual and sex-based pharmacokinetic variability. The plasma and lymphatic pharmacokinetics of PLD were evaluated in male and female rats by quantifying doxorubicin as well as the ³H-labelled liposome. In general, the pharmacokinetics of doxorubicin and the ³H-liposome did not differ significantly between male and female rats when corrected for body surface area. Female rats did, however, show significantly higher doxorubicin concentrations in lymph compared to male rats. With the exception of serum testosterone concentrations in males, none of the physiological parameters evaluated correlated with plasma clearance. Further, reanalysis of published human data that formerly reported sex-differences in PLD plasma clearance similarly revealed no significant differences in PLD plasma clearance between males and females with solid tumours, but increased plasma clearance in patients with Kaposi's sarcoma (generally HIV+/immunocompromised). These data suggest that with the exception of lymphatic exposure, there are unlikely to be significant sex effects in the pharmacokinetics of liposomes, but immune function may contribute to inter individual variability.

DNA Methylation-Based Estimates of Circulating Leukocyte Composition for Predicting Colorectal Cancer Survival: A Prospective Cohort Study

Simple Summary

Inflammation is involved in the evolution of cancer. Leukocytes, of which the proportion can be estimated using epigenome-wide methylation data, may serve as a prognostic marker in colorectal cancer (CRC). Our aim was to investigate whether DNA methylation-based estimates of circulating leukocytes is associated with all-cause and disease-specific mortality in a prospective CRC patients’ cohort. Significant associations with CRC prognosis were observed for CD4+ T cells, CD8+ T cells, B cells, NK cells, and lymphocytes, independent of age, sex, tumor stage, tumor subsite, and therapy. CD4+ T cells outperformed other leukocytes and provided added predictive value in comparison to age, sex, and tumor stage. Although cell counting is commonly used in clinical practice, DNA methylation-estimated cell proportions could be a promising tool in understanding the role of leukocytes as CRC prognostic biomarkers when using stored blood samples.

Abstract

Leukocytes are involved in the progression of colorectal cancer (CRC). The proportion of six major leukocyte subtypes can be estimated using epigenome-wide DNA methylation (DNAm) data from stored blood samples. Whether the composition of circulating leukocytes can be used as a prognostic factor is unclear. DNAm-based leukocyte proportions were obtained from a prospective cohort of 2206 CRC patients. Multivariate Cox regression models and survival curves were applied to assess associations between leukocyte composition and survival outcomes. A higher proportion of lymphocytes, including CD4+ T cells, CD8+ T cells, B cells, and NK cells, was associated with better survival, while a higher proportion of neutrophils was associated with poorer survival. CD4+ T cells outperformed other leukocytes in estimating the patients’ prognosis. Comparing the highest quantile to the lowest quantile of CD4+ T cells, hazard ratios (95% confidence intervals) of all-cause and CRC-specific mortality were 0.59 (0.48, 0.72) and 0.59 (0.45, 0.77), respectively. Furthermore, the association of CD4+ T cells and prognosis was stronger among patients with early or intermediate CRC or patients with colon cancer. In conclusion, the composition of circulating leukocytes estimated from DNAm, particularly the proportions of CD4+ T cells, could be used as promising independent predictors of CRC survival.

Common and Novel Markers for Measuring Inflammation and Oxidative Stress Ex Vivo in Research and Clinical Practice-Which to Use Regarding Disease Outcomes?

Many chronic conditions such as cancer, chronic obstructive pulmonary disease, type-2 diabetes, obesity, peripheral/coronary artery disease and auto-immune diseases are associated with low-grade inflammation. Closely related to inflammation is oxidative stress (OS), which can be either causal or secondary to inflammation. While a low level of OS is physiological, chronically increased OS is deleterious. Therefore, valid biomarkers of these signalling pathways may enable detection and following progression of OS/inflammation as well as to evaluate treatment efficacy. Such biomarkers should be stable and obtainable through non-invasive methods and their determination should be affordable and easy. The most frequently used inflammatory markers include acute-phase proteins, essentially CRP, serum amyloid A, fibrinogen and procalcitonin, and cytokines, predominantly TNFα, interleukins 1β, 6, 8, 10 and 12 and their receptors and IFNγ. Some cytokines appear to be disease-specific. Conversely, OS-being ubiquitous-and its biomarkers appear less disease or tissue-specific. These include lipid peroxidation products, e.g., F2-isoprostanes and malondialdehyde, DNA breakdown products (e.g., 8-OH-dG), protein adducts (e.g., carbonylated proteins), or antioxidant status. More novel markers include also -omics related ones, as well as non-invasive, questionnaire-based measures, such as the dietary inflammatory-index (DII), but their link to biological responses may be variable. Nevertheless, many of these markers have been clearly related to a number of diseases. However, their use in clinical practice is often limited, due to lacking analytical or clinical validation, or technical challenges. In this review, we strive to highlight frequently employed and useful markers of inflammation-related OS, including novel promising markers.

Elevated peripheral absolute monocyte count related to clinicopathological features and poor prognosis in solid tumors: Systematic review, meta-analysis, and meta-regression

BACKGROUND

Absolute monocyte count (AMC) is often used to be assessed in cancer follow-up, which has regained interest as a potential prognostic indicator in many solid tumors, though not consistently or comprehensively. In the present study, we set out to perform a comprehensive meta-analysis of all available data regarding the prognostic significance of AMC in solid tumors. We also evaluated the association between AMC and clinical features in solid tumors.

METHODS

A hazard ratio (HR) and corresponding 95% confidence interval (CI) or a p value (p) from eligible studies were extracted and subsequently pooled analyzed. Subgroup analyses and meta-regression analyses were conducted according to the confounders of included studies. In addition, the relationships between AMC and clinical characteristics were also explored in the meta-analysis.

RESULTS

Overall, ninety-three articles comprising 104 studies with 32229 patients were finally included. The results showed that elevated AMC was associated with worse overall survival (OS) (HR = 1.615; 95% CI: 1.475-1.768; p < 0.001), disease-free survival (DFS) (HR:1.488; 95% CI: 1.357-1.633; p < 0.001), progressive-free survival (PFS) (HR: 1.533; 95% CI: 1.342-1.751; p < 0.001) and cancer-specific survival (CSS) (HR: 1.585; 95% CI: 1.253-2.006; p < 0.001) in non-hematological tumors. Subgroup analyses according to each confounder further proved the consistent prognostic value of AMC in solid tumor outcomes. Moreover, elevated AMC was more likely to be observed in male group and patients with smoking history, and associated with longer tumor length and advanced T stage.

CONCLUSION

In short, the meta-analysis found that elevated AMC might indicate poor long-term outcomes in non-hematologic cancers, thus AMC may be a valuable marker in the prognosis for patients with solid tumors.

The Pan-Immune-Inflammation Value is a new prognostic biomarker in metastatic colorectal cancer: results from a pooled-analysis of the Valentino and TRIBE first-line trials

Background

Immune-inflammatory biomarkers (IIBs) showed a prognostic relevance in patients with metastatic CRC (mCRC). We aimed at evaluating the prognostic power of a new comprehensive biomarker, the Pan-Immune-Inflammation Value (PIV), in patients with mCRC receiving first-line therapy.

Methods

In the present pooled-analysis, we included patients enrolled in the Valentino and TRIBE trials. PIV was calculated as: (neutrophil count × platelet count × monocyte count)/lymphocyte count. A cut-off was determined using the maximally selected rank statistics method. Generalised boosted regression (GBR), the Kaplan–Meier method and Cox hazards regression models were used for survival analyses.

Results

A total of 438 patients were included. Overall, 208 patients (47%) had a low-baseline PIV and 230 (53%) had a high-baseline PIV. Patients with high PIV experienced a worse PFS (HR, 1.66; 95% CI, 1.36–2.03, P < 0.001) and worse OS (HR, 2.01; 95% CI, 1.57–2.57; P < 0.001) compared to patients with low PIV. PIV outperformed the other IIBs in the GBR model and in the multivariable models.

Conclusion

PIV is a strong predictor of survival outcomes with better performance than other well-known IIBs in patients with mCRC treated with first-line therapy. PIV should be prospectively validated to better stratify mCRC patients undergoing first-line therapy.