Resection of rectal metastasis after previous radical surgery for pancreatic cancer: Case report and literature review.

RATIONALE: Pancreatic ductal adenocarcinoma (PDAC) is the main type of pancreatic cancer with a poor prognosis. Rectal metastasis after radical resection of PDAC is comparatively rare, and the understanding of such cases is currently not unified. This study presents the entire process of diagnosis and treatment of a patient with PDAC metastasized to the rectal. We propose the viewpoint of exploring potential biomarkers or establishing effective predictive models to assist in the clinical decision-making of such cases. PATIENT CONCERNS: We present the case of a 71-year-old man with slight abdominal distension and dull pain. He underwent surgical treatment for a malignant tumor of the pancreatic body, which was discovered through computed tomography and magnetic resonance imaging examinations. Nine months after the pancreatectomy, a rectal mass was identified by digital rectal examination and diagnosed as a malignant lesion through a puncture biopsy. After a multidisciplinary joint consultation, the patient underwent radical surgery. It was later confirmed as rectal adenocarcinoma based on postoperative pathological results. DIAGNOSIS: The pathological result after pancreatic surgery was PDAC, which had invaded the peripheral nerves and abdominal arteries. A diagnosis of rectal metastasis was determined ultimately by combining with the medical history and immunohistochemical staining results. INTERVENTIONS AND OUTCOMES: Treatment of the PDAC included laparoscopic resection of the body and tail of the pancreas combined with splenectomy, and postoperative systemic chemotherapy. In addition, treatment of the rectal metastasis included laparoscopic radical resection and postoperative systemic chemotherapy. The patient's current living condition was good. LESSONS: As a rare metastatic site of PDAC, rectal metastasis should be avoided because of misdiagnosis and missed diagnosis. Surgical resection is still an effective treatment strategy for localized pancreatic tumors and isolated metastases. Furthermore, the mining of potential biomarkers or the establishment of predictive models for pancreatic cancer and its metastases may contribute to better clinical decision-making in the future.

Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer.

Introduction: Glucose and glutamine are major carbon and energy sources that promote the rapid proliferation of cancer cells. Metabolic shifts observed on cell lines or mouse models may not reflect the general metabolic shifts in real human cancer tissue. Method: In this study, we conducted a computational characterization of the flux distribution and variations of the central energy metabolism and key branches in a pan-cancer analysis, including the glycolytic pathway, production of lactate, tricarboxylic acid (TCA) cycle, nucleic acid synthesis, glutaminolysis, glutamate, glutamine, and glutathione metabolism, and amino acid synthesis, in 11 cancer subtypes and nine matched adjacent normal tissue types using TCGA transcriptomics data. Result: Our analysis confirms the increased influx in glucose uptake and glycolysis and decreased upper part of the TCA cycle, i.e., the Warburg effect, in almost all the analyzed cancer. However, increased lactate production and the second half of the TCA cycle were only seen in certain cancer types. More interestingly, we failed to detect significantly altered glutaminolysis in cancer tissues compared to their adjacent normal tissues. A systems biology model of metabolic shifts through cancer and tissue types is further developed and analyzed. We observed that (1) normal tissues have distinct metabolic phenotypes; (2) cancer types have drastically different metabolic shifts compared to their adjacent normal controls; and (3) the different shifts in tissue-specific metabolic phenotypes result in a converged metabolic phenotype through cancer types and cancer progression. Discussion: This study strongly suggests the possibility of having a unified framework for studies of cancer-inducing stressors, adaptive metabolic reprogramming, and cancerous behaviors.

Identify potential driver genes for PAX-FOXO1 fusion-negative rhabdomyosarcoma through frequent gene co-expression network mining.

Background: Rhabdomyosarcoma (RMS) is a soft tissue sarcoma usually originated from skeletal muscle. Currently, RMS classification based on PAX-FOXO1 fusion is widely adopted. However, compared to relatively clear understanding of the tumorigenesis in the fusion-positive RMS, little is known for that in fusion-negative RMS (FN-RMS). Methods: We explored the molecular mechanisms and the driver genes of FN-RMS through frequent gene co-expression network mining (fGCN), differential copy number (CN) and differential expression analyses on multiple RMS transcriptomic datasets. Results: We obtained 50 fGCN modules, among which five are differentially expressed between different fusion status. A closer look showed 23% of Module 2 genes are concentrated on several cytobands of chromosome 8. Upstream regulators such as MYC, YAP1, TWIST1 were identified for the fGCN modules. Using in a separate dataset we confirmed that, comparing to FP-RMS, 59 Module 2 genes show consistent CN amplification and mRNA overexpression, among which 28 are on the identified chr8 cytobands. Such CN amplification and nearby MYC (also resides on one of the above cytobands) and other upstream regulators (YAP1, TWIST1) may work together to drive FN-RMS tumorigenesis and progression. Up to 43.1% downstream targets of Yap1 and 45.8% of the targets of Myc are differentially expressed in FN-RMS vs. normal comparisons, which also confirmed the driving force of these regulators. Discussion: We discovered that copy number amplification of specific cytobands on chr8 and the upstream regulators MYC, YAP1 and TWIST1 work together to affect the downstream gene co-expression and promote FN-RMS tumorigenesis and progression. Our findings provide new insights for FN-RMS tumorigenesis and offer promising targets for precision therapy. Experimental investigation about the functions of identified potential drivers in FN-RMS are in progress.

Redundant and Nonredundant Information for Model Calibration or Hydraulic Tomography.

Drawdown data from independent pumping tests have widely been used to validate the estimated hydraulic parameters from inverse modeling or hydraulic tomography (HT). Yet, the independent pumping test has not been clearly defined. Therefore, the goal of this paper is to define this independent pumping test concept, based on the redundant or nonredundant information about aquifer heterogeneity embedded in the observed heads during cross-hole pumping tests. The definition of complete, moderate redundancy and high nonredundancy of information are stipulated using cross-correlation analysis of the relationship between the head and heterogeneity. Afterward, data from numerical experiments and field sequential pumping test campaigns reinforce the concept and the definition.