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Liver metastases from gastrointestinal and non-gastrointestinal malignancies remain a major cause of cancer-related mortality and a major clinical challenge. The liver has unique properties that facilitate metastatic expansion, including a complex immune system that evolved to dampen immunity to neoantigens entering the liver from the gut, through the portal circulation. In this review, we describe the unique microenvironment encountered by cancer cells in the liver, focusing on elements of the innate and adaptive immune response that can act as a double-edge sword, contributing to the elimination of cancer cells on the one hand and promoting their survival and growth, on the other. We discuss this microenvironment in a clinical context, particularly for colorectal carcinoma, and highlight how a better understanding of the role of the microenvironment has spurred an intense effort to develop novel and innovative strategies for targeting liver metastatic disease, some of which are currently being tested in the clinic.
\n \n\n \n \nOBJECTIVE: To systematically review studies reporting clinicopathological features of intraductal papillary neoplasm of the bile duct (IPNB) to provide evidence-based guidance for management. BACKGROUND: IPNB is a rare tumor type. Management decisions are currently based upon anecdotal evidence and small case series. To data, there has been no systematic review of IPNB literature. METHODS: MEDLINE, EMBASE, and the Cochrane Database of Systematic Reviews were searched and data were extracted from relevant studies. Meta-analysis was used to pool study estimates. Evidence of association was determined by comparing pooled crude odds ratios (OR) derived from abstracted data. RESULTS: Fifty-seven retrospective case series were included. At least 43% of 476 specimens contained invasive disease. Invasive tumors were found at significantly higher frequency in pancreaticobiliary than intestinal, gastric or oncocytic-type IPNB [pooled OR 2.5, 95% confidence interval (CI) 1.5-4.2, P < 0.001]. A significantly higher proportion of pancreaticobiliary tumors compared with intestinal tumors expressed MUC-1 [86.4% (95% CI 75.1%-94.7%) vs 13.2% (95% CI 4.6%-25.2%), respectively P < 0.001]. IPNB identified in centers from Asia were more likely to be intrahepatic and were less frequently invasive compared with those from Western centers. Pooled estimates of absolute survival after IPNB resection were 96% (95% CI 93%-99%) at 1 year, 79% (95% CI 69%-88%) at 3 years, and 65% (95% CI 46%-76%) at 5 years. CONCLUSIONS: Early surgery is advisable for radiologically suspected IPNB as it is frequently invasive. The pathobiology of IPNB demonstrates geographic variation. Pancreaticobiliary IPNB expresses MUC1 and is more frequently associated with invasive disease than other IPNB subtypes.
\n \n\n \n \nBACKGROUND: CXCL12 (SDF1) is reported to promote cancer progression in several preclinical models and this is corroborated by the analysis of human tissue specimens. However, the relationship between CXCL12 expression and cancer survival has not been systematically assessed. METHODS: We conducted a systematic review and meta-analysis of studies that evaluated the association between CXCL12 expression and cancer survival. RESULTS: Thirty-eight studies inclusive of 5807 patients were included in the analysis of overall, recurrence-free or cancer-specific survival, the majority of which were retrospective. The pooled hazard ratios (HRs) for overall and recurrence-free survival in patients with high CXCL12 expression were 1.39 (95% CI: 1.17-1.65, P=0.0002) and 1.12 (95% CI: 0.82-1.53, P=0.48) respectively, but with significant heterogeneity between studies. On subgroup analysis by cancer type, high CXCL12 expression was associated with reduced overall survival in patients with oesophagogastric (HR 2.08; 95% CI: 1.31-3.33, P=0.002), pancreatic (HR 1.54; 95% CI: 1.21-1.97, P=0.0005) and lung cancer (HR 1.37; 95% CI: 1.08-1.75, P=0.01), whereas in breast cancer patients high CXCL12 expression conferred an overall survival advantage (HR 0.5; 95% CI: 0.38-0.66, P<0.00001). CONCLUSIONS: Determination of CXCL12 expression has the potential to be of use as a cancer biomarker and adds prognostic information in various cancer types. Prospective or prospective-retrospective analyses of CXCL12 expression in clearly defined cancer cohorts are now required to advance our understanding of the relationship between CXCL12 expression and cancer outcome.
\n \n\n \n \nPURPOSE: Predicting perioperative morbidity and mortality can be achieved by several risk predicting algorithms. In the UK, the National Emergency Laparotomy Audit, mandated for all patients undergoing emergency laparotomy, uses pPOSSUM as its risk prediction tool. However, there is no literature reporting the inter-operator variability in calculating the score. Inter-rater variability was assessed based on 10 real general surgical cases that went on to have an emergency laparotomy. METHODS: Forty clinicians, 10 each of registrars and consultants in anaesthetics and general surgery, were asked to calculate the pPOSSUM based on the clinical information typically available at the time of making the decision to proceed to emergency laparotomy for the same 10 National Emergency Laparotomy Audit cases. All participants were surveyed to assess their understanding and use of the pPOSSUM score. RESULTS: More than 80% of respondents stated that they use pPOSSUM in daily clinical practice. There was variability in the calculated scores between the groups analysed. Two subgroups were evident: one in which the calculated mean pPOSSUM was similar between participants but did not reflect the true value, and the other which was accurate, but demonstrated high inter-rater variability. CONCLUSIONS: This is the first study to investigate inter-operator variability in pPOSSUM scores. Previous reports on the validity of the tool fail to account for subjective variation. At a time where pPOSSUM has become a routine part of clinical practice, this variability needs to be accounted for and taken into consideration in the decision-making process.
\n \n\n \n \nRegulation of the programming of tumour-associated macrophages (TAMs) controls tumour growth and anti-tumour immunity. We examined the role of FGF2 in that regulation. Tumours in mice genetically deficient in low-molecular weight FGF2 (FGF2LMW) regress dependent on T cells. Yet, TAMS not T cells express FGF receptors. Bone marrow derived-macrophages from Fgf2LMW-/- mice co-injected with cancer cells reduce tumour growth and express more inflammatory cytokines. FGF2 is induced in the tumour microenvironment following fractionated radiation in murine tumours consistent with clinical reports. Combination treatment of in vivo tumours with fractionated radiation and a blocking antibody to FGF2 prolongs tumour growth delay, increases long-term survival and leads to a higher iNOS+/CD206+ TAM ratio compared to irradiation alone. These studies show for the first time that FGF2 affects macrophage programming and is a critical regulator of immunity in the tumour microenvironment.
\n \n\n \n \nWhile radical prostatectomy remains the mainstay of prostate cancer (PCa) treatment, 20 to 40% of patients develop postsurgical biochemical recurrence (BCR). A particularly challenging clinical cohort includes patients with intermediate-risk disease whose risk stratification would benefit from advanced approaches that complement standard-of-care diagnostic tools. Here, we show that imaging tumor lactate using hyperpolarized 13C MRI and spatial metabolomics identifies BCR-positive patients in two prospective intermediate-risk surgical cohorts. Supported by spatially resolved tissue analysis of established glycolytic biomarkers, this study provides the rationale for multicenter trials of tumor metabolic imaging as an auxiliary tool to support PCa treatment decision-making.
\n \n\n \n \nGenetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx\u00ae, Decipher\u00ae, Prostadiag\u00ae) using a step-wise approach with increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses.
\n \n\n \n \nBACKGROUND: Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. METHODS: We investigated the association of 2,002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomization (MR) and colocalization. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalization were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumor tissue to assess their role in tumor aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. RESULTS: We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which a majority were novel and replicated. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirm an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also find an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk mapped to existing therapeutic interventions. CONCLUSION: Our findings emphasize the importance of proteomics for improving our understanding of prostate cancer etiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumors. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer.
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