Inflammatory networks cultivate cancer cell metastasis to the liver

Nomogram based on immune-inflammatory indicators and age-adjusted charlson comorbidity index score to predict prognosis of postoperative parotid gland carcinoma patients

BACKGROUND

Parotid gland carcinoma (PGC) is a rare malignant tumor. The purpose of this study was to investigate the role of immune-inflammatory-nutrition indicators and age-adjusted Charlson comorbidity index score (ACCI) of PGC and develop the nomogram model for predicting prognosis.

METHOD

All patients diagnosed with PGC in two tertiary hospitals, treated with surgical resection, from March 2012 to June 2018 were obtained. Potential prognostic factors were identified by univariate and multivariate Cox regression analyses. The nomogram models were established based on these identified independent prognostic factors. The performance of the developed prognostic model was estimated by related indexes and plots.

RESULT

The study population consisted of 344 patients with PGC who underwent surgical resection, 285 patients without smoking (82.8%), and 225 patients (65.4%) with mucoepidermoid carcinoma, with a median age of 50.0 years. American Joint Committee on Cancer (AJCC) stage (p < 0.001), pathology (p = 0.019), tumor location (p < 0.001), extranodal extension (ENE) (p < 0.001), systemic immune-inflammation index (SII) (p = 0.004), prognostic nutrition index (PNI) (p = 0.003), ACCI (p < 0.001), and Glasgow prognostic Score (GPS) (p = 0.001) were independent indicators for disease free survival (DFS). Additionally, the independent prognostic factors for overall survival (OS) including AJCC stage (p = 0.015), pathology (p = 0.004), tumor location (p < 0.001), perineural invasion (p = 0.009), ENE (p < 0.001), systemic immune-inflammation index (SII) (p = 0.001), PNI (p = 0.001), ACCI (p = 0.003), and GPS (p = 0.033). The nomogram models for predicting DFS and OS in PGC patients were generated based on these independent risk factors. All nomogram models show good discriminative capability with area under curves (AUCs) over 0.8 (DFS 0.802, and OS 0.825, respectively). Decision curve analysis (DCA), integrated discrimination improvement (IDI), and net reclassification index (NRI) show good clinical net benefit of the two nomograms in both training and validation cohorts. Kaplan-Meier survival analyses showed superior discrimination of DFS and OS in the new risk stratification system compared with the AJCC stage system. Finally, postoperative patients with PGC who underwent adjuvant radiotherapy had a better prognosis in the high-, and medium-risk subgroups (p < 0.05), but not for the low-risk subgroup.

CONCLUSION

The immune-inflammatory-nutrition indicators and ACCI played an important role in both DFS and OS of PGC patients. Adjuvant radiotherapy had no benefit in the low-risk subgroup for PGC patients who underwent surgical resection. The newly established nomogram models perform well and can provide an individualized prognostic reference, which may be helpful for patients and surgeons in proper follow-up strategies.

Prostate Cancer Liver Metastasis: An Ominous Metastatic Site in Need of Distinct Management Strategies

Prostate cancer liver metastasis (PCLM), seen in upwards of 25% of metastatic castration-resistant PC (mCRPC) patients, is the most lethal site of mCRPC with a median overall survival of 10-14 months. Despite its ominous prognosis and anticipated rise in incidence due to longer survival with contemporary therapy, PCLM is understudied. This review aims to summarize the existing literature regarding the risk factors associated with the development of PCLM, and to identify areas warranting further research. A literature search was conducted through Ovid MEDLINE from 2000 to March 2023. Relevant subject headings and text words were used to capture the following concepts: "Prostatic Neoplasms", "Liver Neoplasms", and "Neoplasm Metastasis". Citation searching identified additional manuscripts. Forty-one studies were retained for detailed analysis. The clinical risk factors for visceral/liver metastasis included <70 years, ≥T3 tumor, N1 nodal stage, de novo metastasis, PSA >20 ng/mL, and a Gleason score >8. Additional risk factors comprised elevated serum AST, LDH or ALP, decreased Hb, genetic markers like RB1 and PTEN loss, PIK3CB and MYC amplification, as well as numerous PC treatments either acting directly or indirectly through inducing liver injury. Further research regarding predictive factors, early detection strategies, and targeted therapies for PCLM are critical for improving patient outcomes.

A novel nomogram and risk classification system based on inflammatory and immune indicators for predicting prognosis of pancreatic cancer patients with liver metastases

BACKGROUND

The study determined to construct a novel predictive nomogram to access the prognosis of pancreatic cancer patients with liver metastases (PCLM).

METHODS

Medical records included clinical and laboratory variables were collected. The patients were randomly divided into training and validation cohort. First, in the training cohort, the optimal cutoff value of SII, PNI, NLR, PLR were obtained. Then the survival analysis evaluated the effects of above indices on OS. Next, univariate and multivariate analyses were used to identify the independent factors of OS. Moreover, a nomogram was constructed based on LASSO cox analysis. Additionally, the predictive efficacy of the nomogram was evaluated by ROC curve and calibration curve in the training and validation cohort. Finally, a risk stratification system based on the nomogram was performed.

RESULTS

A total of 472 PCLM patients were enrolled in the study. The optimal cutoff values of SII, PNI, PLR and NLR were 372, 43.6, 285.7143 and 1.48, respectively. By combing SII and PNI, named coSII-PNI, we divided the patients into three groups. The Kaplan-Meier curves demonstrated above indices were correlated with OS. Univariate and multivariate analyses found the independent prognostic factors of OS. Through LASSO cox analysis, coSII-PNI, PNI, NLR, CA199, CEA, chemotherapy and gender were used to construct the nomogram. Lastly, the ROC curve and calibration curve demonstrated that the nomogram can predict prognosis of PCLM patients. Significant differences were observed between high and low groups.

CONCLUSIONS

The nomogram based on immune, inflammation, nutritional status and other clinical factors can accurately predict OS of PCLM patients.

Tumor Microenvironment in Pancreatic Cancer Pathogenesis and Therapeutic Resistance

Pancreatic ductal adenocarcinoma (PDAC) features a prominent stromal microenvironment with remarkable cellular and spatial heterogeneity that meaningfully impacts disease biology and treatment resistance. Recent advances in tissue imaging capabilities, single-cell analytics, and disease modeling have shed light on organizing principles that shape the stromal complexity of PDAC tumors. These insights into the functional and spatial dependencies that coordinate cancer cell biology and the relationships that exist between cells and extracellular matrix components present in tumors are expected to unveil therapeutic vulnerabilities. We review recent advances in the field and discuss current understandings of mechanisms by which the tumor microenvironment shapes PDAC pathogenesis and therapy resistance.

Serum Amyloid A Proteins and Their Impact on Metastasis and Immune Biology in Cancer

Simple Summary

The liver responds to systemic inflammation and injury in a coordinated manner, called the acute phase response. While this normal physiological response aims to restore homeostasis, malignant transformation coopts this biology to increase the risk for metastasis, immune evasion, and therapeutic resistance. In this Review, we discuss the importance of acute phase response proteins in regulating cancer biology and treatment efficacy. We also consider potential strategies to intervene on acute phase biology as an approach to improve outcomes in cancer.

Abstract

Cancer triggers the systemic release of inflammatory molecules that support cancer cell metastasis and immune evasion. Notably, this biology shows striking similarity to an acute phase response that is coordinated by the liver. Consistent with this, a role for the liver in defining cancer biology is becoming increasingly appreciated. Understanding the mechanisms that link acute phase biology to metastasis and immune evasion in cancer may reveal vulnerable pathways and novel therapeutic targets. Herein, we discuss a link between acute phase biology and cancer with a focus on serum amyloid A proteins and their involvement in regulating the metastatic cascade and cancer immunobiology.

Immune Milieu Established by Postpartum Liver Involution Promotes Breast Cancer Liver Metastasis

In rodents, we identified a physiologic process within the normal liver that creates a pre-metastatic niche. This physiology is weaning-induced liver involution, characterized by hepatocyte cell death, immune influx, and extracellular matrix remodeling. Here, using weaning-induced liver involution as a model of a physiologically regulated pro-metastatic niche, we investigate how liver involution supports breast cancer metastasis. Liver metastases were induced in BALB/c immune competent hosts by portal vein injection of D2OR (low metastatic) or D2A1 (high metastatic) mouse mammary tumor cells. Tumor incidence and multiplicity increased in involution hosts with no evidence of a proliferation advantage. D2OR tumor cell extravasation, seeding, and early survival were not enhanced in the involuting group compared to the nulliparous group. Rather, the involution metastatic advantage was observed at 14 days post tumor cell injection. This metastatic advantage associated with induction of immune tolerance in the involution host liver, reproductive state dependent intra-tumoral immune composition, and CD8-dependent suppression of metastases in nulliparous hosts. Our findings suggest that the normal postpartum liver is in an immune suppressed state, which can provide a pro-metastatic advantage to circulating breast cancer cells. Potential relevance to women is suggested as a postpartum diagnosis of breast cancer is an independent predictor of liver metastasis.

Cell cycle-related kinase reprograms the liver immune microenvironment to promote cancer metastasis

The liver is an immunologically tolerant organ and a common metastatic site of multiple cancer types. Although a role for cancer cell invasion programs has been well characterized, whether and how liver-intrinsic factors drive metastatic spread is incompletely understood. Here, we show that aberrantly activated hepatocyte-intrinsic cell cycle-related kinase (CCRK) signaling in chronic liver diseases is critical for cancer metastasis by reprogramming an immunosuppressive microenvironment. Using an inducible liver-specific transgenic model, we found that CCRK overexpression dramatically increased both B16F10 melanoma and MC38 colorectal cancer (CRC) metastasis to the liver, which was highly infiltrated by polymorphonuclear-myeloid-derived suppressor cells (PMN-MDSCs) and lacking natural killer T (NKT) cells. Depletion of PMN-MDSCs in CCRK transgenic mice restored NKT cell levels and their interferon gamma production and reduced liver metastasis to 2.7% and 0.7% (metastatic tumor weights) in the melanoma and CRC models, respectively. Mechanistically, CCRK activated nuclear factor-kappa B (NF-κB) signaling to increase the PMN-MDSC-trafficking chemokine C-X-C motif ligand 1 (CXCL1), which was positively correlated with liver-infiltrating PMN-MDSC levels in CCRK transgenic mice. Accordingly, CRC liver metastasis patients exhibited hyperactivation of hepatic CCRK/NF-κB/CXCL1 signaling, which was associated with accumulation of PMN-MDSCs and paucity of NKT cells compared to healthy liver transplantation donors. In summary, this study demonstrates that immunosuppressive reprogramming by hepatic CCRK signaling undermines antimetastatic immunosurveillance. Our findings offer new mechanistic insights and therapeutic targets for liver metastasis intervention.