MUC16 and TP53 family co-regulate tumor-stromal heterogeneity in pancreatic adenocarcinoma

Prognosis conferred by molecular features of appendix-derived Pseudomyxoma Peritonei

INTRODUCTION

Pseudomyxoma Peritonei (PMP) is an extremely rare disease characterized by progressive accumulation of mucinous ascites and implants in the peritoneum. We investigated the prognostic value for response to cytoreductive surgery (CRS) or hyperthermic intraperitoneal chemotherapy (HIPEC) and dissected potential beneficial targeted therapy utilizing genomic characteristics.

METHODS

Whole-exome sequencing (WES) was performed on tissue specimens and matched white blood cells from 81 patients with PMP. The study investigated mutational signatures, profiling, and their correlation with progression-free survival (PFS) and overall survival (OS).

RESULTS

Signature 3 (HRD) and signature 15 (dMMR) were dominant. NMF cluster 1, characterized by signature 4, exhibited a worse prognosis. The p53 and TGF-β signaling pathways may contribute as risk factors for worse OS and PFS, respectively. MUC16-mutated patients had worse PFS (P = 0.016) and OS (P = 0.004) compared to wild-type patients. Patients with tumor mutational burden (TMB) > 1(P = 0.026) or alterations in TP53 (P = 0.006) or SMAD4 (P = 0.013) had significantly worse OS compared to those with a TMB < 1 or normal genes. Patients with homologous recombination deficiency (HRD) positivity (P = 0.003) or alterations in TGFBR2 (P = 0.037) experienced worse PFS compared to their respective control groups. Furthermore, NMF cluster1 (P = 0.020), TP53 (P = 0.004), and MUC16 (P = 0.013) were identified as independent prognostic factors for OS, while HRD status (P = 0.003) was independent predictors for PFS in PMP.

CONCLUSIONS

The study reveals that genomic profiling can serve as a robust tool for identifying prognostic markers in PMP. The identified genomic mutations and signaling pathway offer new avenues for targeted therapies.

Leveraging Single-Cell Multi-Omics to Decode Tumor Microenvironment Diversity and Therapeutic Resistance

Recent developments in single-cell multi-omics technologies have provided the ability to identify diverse cell types and decipher key components of the tumor microenvironment (TME), leading to important advancements toward a much deeper understanding of how tumor microenvironment heterogeneity contributes to cancer progression and therapeutic resistance. These technologies are able to integrate data from molecular genomic, transcriptomic, proteomics, and metabolomics studies of cells at a single-cell resolution scale that give rise to the full cellular and molecular complexity in the TME. Understanding the complex and sometimes reciprocal relationships among cancer cells, CAFs, immune cells, and ECs has led to novel insights into their immense heterogeneity in functions, which can have important consequences on tumor behavior. In-depth studies have uncovered immune evasion mechanisms, including the exhaustion of T cells and metabolic reprogramming in response to hypoxia from cancer cells. Single-cell multi-omics also revealed resistance mechanisms, such as stromal cell-secreted factors and physical barriers in the extracellular matrix. Future studies examining specific metabolic pathways and targeting approaches to reduce the heterogeneity in the TME will likely lead to better outcomes with immunotherapies, drug delivery, etc., for cancer treatments. Future studies will incorporate multi-omics data, spatial relationships in tumor micro-environments, and their translation into personalized cancer therapies. This review emphasizes how single-cell multi-omics can provide insights into the cellular and molecular heterogeneity of the TME, revealing immune evasion mechanisms, metabolic reprogramming, and stromal cell influences. These insights aim to guide the development of personalized and targeted cancer therapies, highlighting the role of TME diversity in shaping tumor behavior and treatment outcomes.

Pancreatic ductal adenocarcinoma microenvironment: Soluble factors and cancer associated fibroblasts as modulators of NK cell functions

Pancreatic Ductal Adenocarcinoma (PDAC) is the most frequent pancreatic cancer and represents one of the most aggressive human neoplasms. Typically identified at advance stage disease, most PDAC tumors are unresectable and resistant to standard therapies. The immunosuppressive microenvironment in PDAC impedes tumor control but a greater understanding of the complex stromal interactions within the tumor microenvironment (TME) and the development of strategies capable of restoring antitumor effector immune responses could be crucial to fight this aggressive tumor and its spread. Natural Killer (NK) cells play a crucial role in cancer immunosurveillance and represent an attractive target for immunotherapies, both as cell therapy and as a pharmaceutical target. This review describes some crucial components of the PDAC TME (collagens, soluble factors and fibroblasts) that can influence the presence, phenotype and function of NK cells in PDAC patients tumor tissue. This focused overview highlights the therapeutic relevance of dissecting the complex stromal composition to define new strategies for NK cell-based immunotherapies to improve the treatment of PDAC.

Predicting Survival Signature of Bladder Cancer Related to Cancer-Associated Fibroblast (CAF) Constructed by Intersecting Genes in TCGA and GEO

Bladder cancer was one of the most common carcinomas around the world. However, the mechanism of the disease still remained to be investigated. We expected to establish a prognostic survival model with 9 prognostic genes to predict overall survival (OS) in patients of bladder cancer. The gene expression data of bladder cancer were obtained from TCGA and GEO datasets. TCGA and GEO datasets were used for screening prognostic genes along with developing and validating a 9-gene prognostic survival model by method of weighted gene co-expression network analysis (WGCNA) and LASSO with Cox regression. The relative analysis of evaluate tumor burden mutation (TBM), GO, KEGG, chemotherapy drug and functional pathway were also performed based on CAF-related mRNAs. 151 Overlapping CAF-related genes were distinguished after intersecting differentially expressed genes from 945 genes in TCGA and 491 genes in GEO dataset. 9 Prognostic genes (MSRB2, AGMAT, KLF6, DDAH2, GADD45B, SERPINE2, STMN3, TEAD2, and COMP) were used for construction of prognostic model after LASSO with Cox regression. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. Functional analysis indicated chemokine, cytokine, ECM interaction, oxidative stress and apoptosis were highly appeared. Potential drugs targeted different CAF-related genes like vemurafenib, irofulven, ghiotepa, and idarubicin were found as well. We constructed a novel 9 CAF-related mRNAs prognostic model and explored the gene expression and potential functional information of related genes, which might be worthy of clinical application. In addition, potential chemotherapy drugs could provide useful insights into the potential clinical treatment of bladder cancer.

MUC1 and MUC16: critical for immune modulation in cancer therapeutics

The Mucin (MUC) family, a range of highly glycosylated macromolecules, is ubiquitously expressed in mammalian epithelial cells. Such molecules are pivotal in establishing protective mucosal barriers, serving as defenses against pathogenic assaults. Intriguingly, the aberrant expression of specific MUC proteins, notably Mucin 1 (MUC1) and Mucin 16 (MUC16), within tumor cells, is intimately associated with oncogenesis, proliferation, and metastasis. This association involves various mechanisms, including cellular proliferation, viability, apoptosis resistance, chemotherapeutic resilience, metabolic shifts, and immune surveillance evasion. Due to their distinctive biological roles and structural features in oncology, MUC proteins have attracted considerable attention as prospective targets and biomarkers in cancer therapy. The current review offers an exhaustive exploration of the roles of MUC1 and MUC16 in the context of cancer biomarkers, elucidating their critical contributions to the mechanisms of cellular signal transduction, regulation of immune responses, and the modulation of the tumor microenvironment. Additionally, the article evaluates the latest advances in therapeutic strategies targeting these mucins, focusing on innovations in immunotherapies and targeted drugs, aiming to enhance customization and accuracy in cancer treatments.

Combination of mutations in genes controlling DNA repair and high mutational load plays a prognostic role in pancreatic ductal adenocarcinoma (PDAC): a retrospective real-life study in Sardinian population

BACKGROUND

Patients with pancreatic ductal adenocarcinoma (PDCA) carrying impaired mismatch repair mechanisms seem to have an outcome advantage under treatment with conventional chemotherapy, whereas the role for the tumor mutation burden on prognosis is controversial. In this study, we evaluated the prognostic role of the mutated genes involved in genome damage repair in a real-life series of PDAC patients in a hospital-based manner from the main Institution deputed to surgically treat such a disease in North Sardinia.

METHODS

A cohort of fifty-five consecutive PDAC patients with potentially resectable/border line resectable PDAC (stage IIB-III) or oligometastatic disease (stage IV) and tumor tissue availability underwent next-generation sequencing (NGS)-based analysis using a panel containing driver oncogenes and tumor suppressor genes as well as genes controlling DNA repair mechanisms.

RESULTS

Genes involved in the both genome damage repair (DR) and DNA mismatch repair (MMR) were found mutated in 17 (31%) and 15 (27%) cases, respectively. One fourth of PDAC cases (14/55; 25.5%) carried tumors presenting a combination of mutations in repair genes (DR and MMR) and the highest mutation load rates (MLR-H). After correction for confounders (surgery, adjuvant therapy, stage T, and metastasis), multivariate Cox regression analysis indicated that mutations in DR genes (HR = 3.0126, 95% CI 1.0707 to 8.4764, p = 0.0367) and the MLR (HR = 1.0018, 95%CI 1.0005 to 1.0032, p = 0.009) were significantly related to worse survival.

CONCLUSIONS

The combination of mutated repair genes and MLR-H, which is associated with a worse survival in our series of PDAC patients treated with conventional chemotherapy protocols, might become a predictive biomarker of response to immunotherapy in addition to its prognostic role in predicting survival.