Evolution of Rapid Clonal Dynamics and Non-Cross-Resistance in Response to Alternating Targeted Therapy and Chemotherapy in BRAF-V600E-Mutant Colon Cancer.

Purpose: Combined BRAF, MEK, and EGFR inhibition can induce clinical responses in BRAF-V600E-mutant colon cancer, but rapid resistance often occurs.

Methods: We use serial monitoring of circulating tumor DNA cell-free plasma DNA (cfDNA) in a patient case study in addition to organoids derived from mouse models of BRAF-V600E-mutant intestinal cancer, which emulated the patient's mutational profile to assess drug treatment efficacy.

Results: We demonstrate dynamic evolution of resistance to combined EGFR/BRAF/MEK inhibition in a pediatric patient with metastatic BRAF-V600E-mutant, mismatch repair-stable colon cancer.

Error-prone repair of stalled replication forks drives mutagenesis and loss of heterozygosity in haploinsufficient BRCA1 cells.

Germline mutations in the BRCA genes are associated with a higher risk of carcinogenesis, which is linked to an increased mutation rate and loss of the second unaffected BRCA allele (loss of heterozygosity, LOH). However, the mechanisms triggering mutagenesis are not clearly understood. The BRCA genes contain high numbers of repetitive DNA sequences.

Germline Testing Data Validate Inferences of Mutational Status for Variants Detected From Tumor-Only Sequencing.

Unlabelled: Pathogenic germline variants (PGVs) in cancer susceptibility genes are usually identified through germline testing of DNA from blood or saliva: their detection can affect treatment options and potential risk-reduction strategies for patient relatives. PGV can also be identified in tumor sequencing assays, which, when performed without patient-matched normal specimens, render determination of variants' germline or somatic origin critical.

Methods: Tumor-only sequencing data from 1,608 patients were retrospectively analyzed to infer germline versus somatic status of variants using an information-theoretic, gene-independent approach.

Wearable sensors for the monitoring of movement disorders.

This paper offers a review of the implementation of current wearable sensing technologies in monitoring the movement and activity of patients suffering from movement disorders. Recent literature has focused on incorporating simple and reliable wearable technologies for the continuous and objective monitoring of patient movement during normal daily activities. However, the use of such wearable sensing technologies has yet to find its way to clinical practice.

Activity Recognition Using Complex Network Analysis.

In this paper, we perform complex network analysis on a connectivity dataset retrieved from a monitoring system in order to classify simple daily activities. The monitoring system is composed of a set of wearable sensing modules positioned on the subject's body and the connectivity data consists of the correlation between each pair of modules. A number of network measures are then computed followed by the application of statistical significance and feature selection methods.

Detection of Levodopa Induced Dyskinesia in Parkinson's Disease patients based on activity classification.

In this paper, we present an activity classification-based algorithm for the automatic detection of Levodopa Induced Dyskinesia in Parkinson's Disease (PD) patients. Two PD patients experiencing motor fluctuations related to chronic Levodopa therapy performed a protocol of simple daily life activities on at least two different occasions. A Random Forest classifier was able to classify the performed activities by the patients with an overall accuracy of 86%.