Automation in optometry (the implications and impact) and the use of computers in optometry

Automation in optometry (the implications and impact) and the use of computers in optometr

Optimizing Circulating Tumour DNA Use in the Perioperative Setting for Intrahepatic Cholangiocarcinoma: Diagnosis, Screening, Minimal Residual Disease Detection and Treatment Response Monitoring

In this review, we present the current evidence and future perspectives on the use of circulating tumour DNA (ctDNA) in the diagnosis, management and understanding the prognosis of patients with intrahepatic cholangiocarcinoma (iCCA) undergoing surgery. Liquid biopsies or ctDNA maybe utilized to: (1) determine the molecular profile of the tumour and therefore guide the selection of molecular targeted therapy in the neoadjuvant setting, (2) form a surveillance tool for the detection of minimal residual disease or cancer recurrence after surgery, and (3) diagnose and screen for early iCCA detection in high-risk populations. The potential for ctDNA can be tumour-informed or -uninformed depending on the goals of its use. Future studies will require ctDNA extraction technique validations, with standardizations of both the platforms and the timing of ctDNA collections

Exome sequencing identifies nonsegregating nonsense ATM and PALB2 variants in familial pancreatic cancer.

We sequenced 11 germline exomes from five families with familial pancreatic cancer (FPC). One proband had a germline nonsense variant in ATM with somatic loss of the variant allele. Another proband had a nonsense variant in PALB2 with somatic loss of the variant allele. Both variants were absent in a relative with FPC. These findings question the causal mechanisms of ATM and PALB2 in these families and highlight challenges in identifying the causes of familial cancer syndromes using exome sequencing

Combined burden and functional impact tests for cancer driver discovery using DriverPower

The discovery of driver mutations is one of the key motivations for cancer genome sequencing. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we describe DriverPower, a software package that uses mutational burden and functional impact evidence to identify driver mutations in coding and non-coding sites within cancer whole genomes. Using a total of 1373 genomic features derived from public sources, DriverPower's background mutation model explains up to 93% of the regional variance in the mutation rate across multiple tumour types. By incorporating functional impact scores, we are able to further increase the accuracy of driver discovery. Testing across a collection of 2583 cancer genomes from the PCAWG project, DriverPower identifies 217 coding and 95 non-coding driver candidates. Comparing to six published methods used by the PCAWG Drivers and Functional Interpretation Working Group, DriverPower has the highest F1 score for both coding and non-coding driver discovery. This demonstrates that DriverPower is an effective framework for computational driver discovery

Validation of four candidate pancreatic cancer serological biomarkers that improve the performance of CA19.9

Abstract Background The identification of new serum biomarkers with high sensitivity and specificity is an important priority in pancreatic cancer research. Through an extensive proteomics analysis of pancreatic cancer cell lines and pancreatic juice, we previously generated a list of candidate pancreatic cancer biomarkers. The present study details further validation of four of our previously identified candidates: regenerating islet-derived 1 beta (REG1B), syncollin (SYCN), anterior gradient homolog 2 protein (AGR2), and lysyl oxidase-like 2 (LOXL2). Methods The candidate biomarkers were validated using enzyme-linked immunosorbent assays in two sample sets of serum/plasma comprising a total of 432 samples (Sample Set A: pancreatic ductal adenocarcinoma (PDAC, n = 100), healthy (n = 92); Sample Set B: PDAC (n = 82), benign (n = 41), disease-free (n = 47), other cancers (n = 70)). Biomarker performance in distinguishing PDAC from each control group was assessed individually in the two sample sets. Subsequently, multiparametric modeling was applied to assess the ability of all possible two and three marker panels in distinguishing PDAC from disease-free controls. The models were generated using sample set B, and then validated in Sample Set A. Results Individually, all markers were significantly elevated in PDAC compared to healthy controls in at least one sample set (p ≤ 0.01). SYCN, REG1B and AGR2 were also significantly elevated in PDAC compared to benign controls (p ≤ 0.01), and AGR2 was significantly elevated in PDAC compared to other cancers (p \u3c 0.01). CA19.9 was also assessed. Individually, CA19.9 showed the greatest area under the curve (AUC) in receiver operating characteristic (ROC) analysis when compared to the tested candidates; however when analyzed in combination, three panels (CA19.9 + REG1B (AUC of 0.88), CA19.9 + SYCN + REG1B (AUC of 0.87) and CA19.9 + AGR2 + REG1B (AUC of 0.87)) showed an AUC that was significantly greater (p \u3c 0.05) than that of CA19.9 alone (AUC of 0.82). In a comparison of early-stage (Stage I-II) PDAC to disease free controls, the combination of SYCN + REG1B + CA19.9 showed the greatest AUC in both sample sets, (AUC of 0.87 and 0.92 in Sets A and B, respectively). Conclusions Additional serum biomarkers, particularly SYCN and REG1B, when combined with CA19.9, show promise as improved diagnostic indicators of pancreatic cancer, which therefore warrants further validation

ID1 and ID3 Regulate the Self-Renewal Capacity of Human Colon Cancer-Initiating Cells through p21

SummaryThere is increasing evidence that some cancers are hierarchically organized, sustained by a relatively rare population of cancer-initiating cells (C-ICs). Although the capacity to initiate tumors upon serial transplantation is a hallmark of all C-ICs, little is known about the genes that control this process. Here, we establish that ID1 and ID3 function together to govern colon cancer-initiating cell (CC-IC) self-renewal through cell-cycle restriction driven by the cell-cycle inhibitor p21. Regulation of p21 by ID1 and ID3 is a central mechanism preventing the accumulation of excess DNA damage and subsequent functional exhaustion of CC-ICs. Additionally, silencing of ID1 and ID3 increases sensitivity of CC-ICs to the chemotherapeutic agent oxaliplatin, linking tumor initiation function with chemotherapy resistance