Purpose: A73-year-old woman with metastatic colon cancer experienced a complete response to chemotherapy with dose-intensified irinotecan that has been durable for 5 years. We sequenced her tumor and germ line DNA and looked for similar patterns in publicly available genomic data from patients with colorectal cancer.

Patients And Methods: Tumor DNA was obtained from a biopsy before therapy, and germ line DNA was obtained from blood. Tumor and germline DNA were sequenced using a commercial panel with approximately 250 genes. Whole-genome amplification and exome sequencing were performed for and . A mutation was confirmed by Sanger sequencing. The somatic mutation and clinical annotation data files from the colon (n = 461) and rectal (n = 171) adenocarcinoma data sets were downloaded from The Cancer Genome Atlas data portal and analyzed for patterns of mutations and clinical outcomes in patients with - and/or -mutated tumors.

Results: The pattern of alterations included biallelic inactivation and microsatellite instability high (MSI-H) phenotype, with somatic inactivation of and hypermutation (estimated mutation rate > 200 per megabase). The extremely high mutation rate led us to investigate additional mechanisms for hypermutation, including loss of function of was unaltered, but a related gene not typically associated with somatic mutation in colon cancer, , had a somatic mutation c.2171G>A[p.Gly724Glu]. Additionally, we noted that the high mutation rate was largely composed of dinucleotide deletions. A similar pattern of hypermutation (dinucleotide deletions, mutations, MSI-H) was found in tumors from The Cancer Genome Atlas.

Conclusion: mutation with associated MSI-H and hyper-indel-hypermutated cancer genome characterizes a previously unrecognized variant of colon cancer that was found in this patient with an exceptional response to chemotherapy.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042871PMC
http://dx.doi.org/10.1200/PO.16.00015DOI Listing

Publication Analysis

Top Keywords

cancer genome
16
colon cancer
12
somatic mutation
12
mutation rate
12
cancer
8
hyper-indel-hypermutated cancer
8
response chemotherapy
8
germ dna
8
mutation
8
high mutation
8

Similar Publications

Large-scale gene-environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often-elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)-based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL-cholesterol (HDL-C).

View Article and Find Full Text PDF

Technological advances in clinical individualized medication for cancer therapy: from genes to whole organism.

Per Med

January 2025

Department of Clinical Pharmacy, Zhejiang Provincial Key Laboratory for Drug Evaluation and Clinical Research, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Efforts have been made to leverage technology to accurately identify tumor characteristics and predict how each cancer patient may respond to medications. This involves collecting data from various sources such as genomic data, histological information, functional drug profiling, and drug metabolism using techniques like polymerase chain reaction, sanger sequencing, next-generation sequencing, fluorescence in situ hybridization, immunohistochemistry staining, patient-derived tumor xenograft models, patient-derived organoid models, and therapeutic drug monitoring. The utilization of diverse detection technologies in clinical practice has made "individualized treatment" possible, but the desired level of accuracy has not been fully attained yet.

View Article and Find Full Text PDF

Objectives: This pilot study aimed to identify early predictors of drug retention in patients with clinically active peripheral psoriatic arthritis who initiated or switched to therapy with biologic and targeted synthetic disease-modifying antirheumatic drugs (bDMARDs and tsDMARDs).

Methods: Clinical and ultrasound assessments were conducted at baseline (t0) and subsequently at 1 (t1), 3 (t3), and 6 (t6) months. Ultrasound evaluations targeted joints/entheses according to PsASon-Score13 and the most clinically involved joint/enthesis/tendon or the two most clinically involved joints/entheses/tendons (MIJET and 2MIJET).

View Article and Find Full Text PDF

Background: Pancreatic cancer is highly aggressive and has a low survival rate primarily due to late-stage diagnosis and the lack of effective early detection methods. We introduce here a novel, noninvasive urinary extracellular vesicle miRNA-based assay for the detection of pancreatic cancer from early to late stages.

Methods: From September 2019 to July 2023, Urine samples were collected from patients with pancreatic cancer (n = 153) from five distinct sites (Hokuto Hospital, Kawasaki Medical School Hospital, National Cancer Center Hospital, Kagoshima University Hospital, and Kumagaya General Hospital) and non-cancer participants (n = 309) from two separate sites (Hokuto Hospital and Omiya City Clinic).

View Article and Find Full Text PDF

The integration of conventional omics data such as genomics and transcriptomics data into artificial intelligence models has advanced significantly in recent years; however, their low applicability in clinical contexts, due to the high complexity of models, has been limited in their direct use inpatients. We integrated classic omics, including DNA mutation and RNA gene expression, added a novel focus on promising omics methods based on A>I(G) RNA editing, and developed a drug response prediction model. We analyzed 104 patients from the Breast Cancer Genome-Guided Therapy Study (NCT02022202).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!