Immune microenvironment of hepatocellular carcinoma,intrahepatic cholangiocarcinoma and liver metastasis of colorectal adenocarcinoma: Relationship with histopathological and molecular classifications

Tumor tissue is composed of tumor cells and tumor stroma. Tumor stroma contains various immune cells and non-immune stromal cells, forming a complex tumor microenvironment which plays pivotal roles in regulating tumor growth. Recent successes in immunotherapies against tumors, including immune checkpoint inhibitors, have further raised interests in the immune microenvironment of liver carcinoma. The immune microenvironment of tumors is formed because of interactions among tumor cells, immune cells and non-immune stromal cells, including fibroblasts and endothelial cells. Different patterns of immune microenvironment are observed among different tumor subtypes, and their clinicopathological significance and intertumor/intratumor heterogeneity are being intensively studied. Here, we review the immune microenvironment of hepatocellular carcinoma, intrahepatic cholangiocarcinoma and liver metastasis of colorectal adenocarcinoma, focusing on its histopathological appearance, clinicopathological significance, and relationship with histological and molecular classifications. Understanding the comprehensive histopathological picture of a tumor immune microenvironment, in addition to molecular and genetic approaches, will further potentiate the effort for precision medicine in the era of tumor-targeting immunotherapy.     

Pharmacokinetic study of the oral fluorouracil antitumor agent S‐1 in patients with impaired renal function

Although dose reduction of S‐1 is recommended for patients with impaired renal function, dose modification for such patients has not been prospectively evaluated. The aim of the present study was to investigate the pharmacokinetic parameters of 5‐fluorouracil, 5‐chloro‐2,4 dihydroxypyridine and oteracil potassium, and to review the recommended dose modification of S‐1 in patients with renal impairment. We classified patients receiving S‐1 into 4 groups according to their renal function, as measured using the Japanese estimated glomerular filtration rate (eGFR) equation. The daily S‐1 dose was adjusted based on the patient's eGFR and body surface area. Blood samples were collected for pharmacokinetic analysis. A total of 33 patients were enrolled and classified into 4 groups as follows: 10 patients in cohort 1 (eGFR ≥ 80 mL/min/1.73 m²), 10 patients in cohort 2 (eGFR = 50‐79 mL/min/1.73 m²), 10 patients in cohort 3 (eGFR = 30‐49 mL/min/1.73 m²), and 3 patients in cohort 4 (eGFR < 30 mL/min/1.73 m²). Those in cohorts 3 and 4 treated with an adjusted dose of S‐1 showed a similar area under the curve for 5‐fluorouracil (941.9 ± 275.6 and 1043.5 ± 224.8 ng/mL, respectively) compared with cohort 2 (1034.9 ± 414.3 ng/mL). Notably, while there was a statistically significant difference between cohort 1 (689.6 ± 208.8 ng/mL) and 2 (P = 0.0474) treated with an equal dose of S‐1, there was no significant difference observed in the toxicity profiles of the cohorts. In conclusion, dose adjustment of S‐1 in patients with impaired renal function using eGFR is appropriate and safe.     

Solid‐type poorly differentiated adenocarcinoma of the stomach: Deficiency of mismatch repair and SWI/SNF complex

ARID1A, one of the subunits in SWI/SNF chromatin remodeling complex, is frequently mutated in gastric cancers with microsatellite instability (MSI). The most frequent MSI in solid‐type poorly differentiated adenocarcinoma (PDA) has been reported, but the SWI/SNF complex status in solid‐type PDA is still largely unknown. We retrospectively analyzed 54 cases of solid‐type PDA for the expressions of mismatch repair (MMR) proteins (MLH1, PMS2, MSH2, and MSH6), SWI/SNF complex subunits (ARID1A, INI1, BRG1, BRM, BAF155, and BAF170) and EBER, and mutations in KRAS and BRAF. We analyzed 40 cases of another histological type of gastric cancer as a control group. The solid‐type PDAs showed coexisting glandular components (76%), MMR deficiency (39%), and complete/partial loss of ARID1A (31%/7%), INI1 (4%/4%), BRG1 (48%/30%), BRM (33%/33%), BAF155 (13%/41%), and BAF170 (6%/2%), EBER positivity (4%), KRAS mutation (2%), and BRAF mutation (2%). Compared to the control group, MMR deficiency and losses of ARID1A, BRG1, BRM, and BAF155 were significantly frequent in solid‐type PDAs. Mismatch repair deficiency was associated with the losses of ARID1A, BRG1, and BAF155 in solid‐type PDAs. In the MMR‐deficient group, solid components showed significantly more frequent losses of ARID1A, BRG1, BRM, and BAF155 compared to glandular components (P = .0268, P = .0181, P = .0224, and P = .0071, respectively). In the MMR‐proficient group, solid components showed significantly more frequent loss of BRG1 compared to glandular components (P = .012). In conclusion, solid‐type PDAs showed frequent losses of MMR proteins and the SWI/SNF complex. We suggest that loss of the SWI/SNF complex could induce a morphological shift from differentiated‐type adenocarcinoma to solid‐type PDA.     

Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot–savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm³. With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.     

Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.     

Dying is the Most Grown-Up Thing We Ever Do: But Do Health Care Professionals Prevent Us from Taking It Seriously?

This paper takes a somewhat slant perspective on flourishing and care in the context of suffering, death and dying, arguing that care in this context consists principally of ‘acts of work and courage that enable flourishing’. Starting with the perception that individuals, society and health care professionals have become dulled to death and the process of dying in Western advanced health systems, it suggests that for flourishing to occur, both of these aspects of life need to be faced more directly. The last days of life need to be ‘undulled’. Reflections upon the experiences of the author as carer and daughter in the face of her mother’s experience of death are used as basis for making suggestions about how care systems and professionals might better assist people in dealing with ‘the most grown up thing’ humans ever do, which is to die.     

Nanomedicines: From Bench to Bedside and Beyond

Advancing nanomedicines from concept to clinic requires integration of new science with traditional pharmaceutical development. The medical and commercial success of nanomedicines is greatly facilitated when those charged with developing nanomedicines are cognizant of the unique opportunities and technical challenges that these products present. These individuals must also be knowledgeable about the processes of clinical and product development, including regulatory considerations, to maximize the odds for successful product registration. This article outlines these topics with a goal to accelerate the combination of academic innovation with collaborative industrial scientists who understand pharmaceutical development and regulatory approval requirements—only together can they realize the full potential of nanomedicines for patients.