The immunomodulatory role of paracrine signalling factor VSIG4 in peritoneal metastases.

Peritoneal metastasis (PM), the regional progression of intra-abdominal malignancies, is a common sequelae of colorectal cancer (CRC). Immunotherapy is slated to be effective in generating long-lasting anti-tumour response as it utilizes the specificity and memory of the immune system. In the tumour microenvironment, tumour associated macrophages (TAMs) are posited to create an anti-inflammatory pro-tumorigenic environment.

Transcriptomic convergence despite genomic divergence drive field cancerization in synchronous squamous tumors.

Introduction: Field cancerization is suggested to arise from imbalanced differentiation in individual basal progenitor cells leading to clonal expansion of mutant cells that eventually replace the epithelium, although without evidence.

Methods: We performed deep sequencing analyses to characterize the genomic and transcriptomic landscapes of field change in two patients with synchronous aerodigestive tract tumors.

Results: Our data support the emergence of numerous genetic alterations in cancer-associated genes but refutes the hypothesis that founder mutation(s) underpin this phenomenon.

Generating patient-derived ascites-dependent xenograft mouse models of peritoneal carcinomatosis.

Clinically relevant animal models are crucial for effective development of therapeutics for peritoneal carcinomatosis (PC). This protocol describes the generation of patient-derived ascites-dependent xenograft (PDADX) models from the cellular component of ascites. The use of routine intraperitoneal injection of the fluid component of ascites is analogous to the biological events occurring intra-abdominally in patients with PC.

Ligand-mediated PAI-1 inhibition in a mouse model of peritoneal carcinomatosis.

Peritoneal carcinomatosis (PC) present a ubiquitous clinical conundrum in all intra-abdominal malignancies. Via functional and transcriptomic experiments of ascites-treated PC cells, we identify STAT3 as a key signaling pathway. Integrative analysis of publicly available databases and correlation with clinical cohorts (n = 7,359) reveal putative clinically significant activating ligands of STAT3 signaling.

A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer.

Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to identify a set of molecular markers for predicting platinum sensitivity.

Gene Expression Changes Associated with Dedifferentiation in Liposarcoma Predict Overall Survival.

Up to 10% of well-differentiated liposarcoma (WDLS) progress to dedifferentiated liposarcoma (DDLS). We aimed to identify gene expression changes associated with dedifferentiation and whether these were informative of tumour biology of DDLS. We analysed datasets from the Gene Expression Omnibus (GEO, ID = GSE30929) database to identify differentially expressed genes between WDLS ( = 52) and DDLS ( = 39).

Postoperative Inflammatory Marker Surveillance in Colorectal Peritoneal Carcinomatosis.

Background: The prognostic significance of inflammatory markers in solid cancers is well-established, albeit with considerable heterogeneity. This study sought to investigate the postoperative inflammatory marker trend in peritoneal carcinomatosis (PC), with a focus on colorectal PC (CPC), and to propose optimal surveillance periods and cutoffs.

Methods: Data were collected from a prospectively maintained database of PC patients treated at the authors' institution from April 2001 to March 2019.

Pairing a prognostic target with potential therapeutic strategy for head and neck cancer.

Objectives: We have previously identified and validated a panel of molecular prognostic markers (ATP13A3, SSR3, and ANO1) for Head and Neck Squamous Cell Carcinoma (HNSCC). The aim of this study was to investigate the consequence of ATP13A3 dysregulation on signaling pathways, to aid in formulating a therapeutic strategy targeting ATP13A3-overexpressing HNSCC.

Materials And Methods: Gene Set Enrichment Analysis (GSEA) was performed on HNSCC microarray expression data (Internal local dataset [n = 92], TCGA [n = 232], EMBL [n = 81]) to identify pathways associated with high expression of ATP13A3.

Axillary Lymph Node Dissection in Angiosarcomas of the Breast: An Asian Institutional Perspective.

Angiosarcomas of the breast (ASB) are rare, making up to less than 8% of all angiosarcomas. The surgical management for this disease continues to vary throughout centres worldwide due to the current limited evidence. We aim to examine the necessity of axillary lymph node dissection in this pathology through a retrospective study of axillary metastasis and recurrence patterns in patients treated at our institution.

An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours.

Generation of large amounts of genomic data is now feasible and cost-effective with improvements in next generation sequencing (NGS) technology. Ribonucleic acid sequencing (RNA-Seq) is becoming the preferred method for comprehensively characterising global transcriptome activity. Unique to cytoreductive surgery (CRS), multiple spatially discrete tumour specimens could be systematically harvested for genomic analysis.

A set of molecular markers predicts chemosensitivity to Mitomycin-C following cytoreductive surgery and hyperthermic intraperitoneal chemotherapy for colorectal peritoneal metastasis.

Cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) is associated with significant perioperative morbidity and mortality. We aim to generate and validate a biomarker set predicting sensitivity to Mitomycin-C to refine selection of patients with colorectal peritoneal metastasis (CPM) for this treatment. A signature predicting Mitomycin-C sensitivity was generated using data from Genomics of Drug Sensitivity in Cancer and The Cancer Genome Atlas.