Genome-wide association study identified copy number variants associated with sporadic colorectal cancer risk

Maternal Copy Number Imbalances in Non-Invasive Prenatal Testing: Do They Matter?

Non-invasive prenatal testing (NIPT) has become a routine practice in screening for common aneuploidies of chromosomes 21, 18, and 13 and gonosomes X and Y in fetuses worldwide since 2015 and has even expanded to include smaller subchromosomal events. In fact, the fetal fraction represents only a small proportion of cell-free DNA on a predominant background of maternal DNA. Unlike fetal findings that have to be confirmed using invasive testing, it has been well documented that NIPT provides information on maternal mosaicism, occult malignancies, and hidden health conditions due to copy number variations (CNVs) with diagnostic resolution. Although large duplications or deletions associated with certain medical conditions or syndromes are usually well recognized and easy to interpret, very little is known about small, relatively common copy number variations on the order of a few hundred kilobases and their potential impact on human health. We analyzed data from 6422 NIPT patient samples with a CNV detection resolution of 200 kb for the maternal genome and identified 942 distinct CNVs; 328 occurred repeatedly. We defined them as multiple occurring variants (MOVs). We scrutinized the most common ones, compared them with frequencies in the gnomAD SVs v2.1, dbVar, and DGV population databases, and analyzed them with an emphasis on genomic content and potential association with specific phenotypes.

Advances in colorectal cancer genomics and transcriptomics drive early detection and prevention

Colorectal carcinoma (CRC) is a high incidence cancer and leading cause of cancer mortality worldwide. The advances in genomics and transcriptomics in the past decades have improved the detection and prevention of CRC in familial CRC syndromes. Nevertheless, the ultimate goal of personalized medicine for sporadic CRC is still not within reach due no less to the difficulty in integrating population disparity and clinical data to combat what essentially is a very heterogenous disease. This minireview highlights the achievement of the past decades and present possible direction in the hope of early detection and metastasis prevention for reducing CRC-associated morbidity and mortality.

RKDOSCNV: A Local Kernel Density-Based Approach to the Detection of Copy Number Variations by Using Next-Generation Sequencing Data

Copy number variations (CNVs) are significant causes of many human cancers and genetic diseases. The detection of CNVs has become a common method by which to analyze human diseases using next-generation sequencing (NGS) data. However, effective detection of insignificant CNVs is still a challenging task. In this study, we propose a new detection method, RKDOSCNV, to meet the need. RKDOSCNV uses kernel density estimation method to evaluate the local kernel density distribution of each read depth segment (RDS) based on an expanded nearest neighbor (k-nearest neighbors, reverse nearest neighbors, and shared nearest neighbors of each RDS) data set, and assigns a relative kernel density outlier score (RKDOS) for each RDS. According to the RKDOS profile, RKDOSCNV predicts the candidate CNVs by choosing a reasonable threshold, which it uses split read approach to correct the boundaries of candidate CNVs. The performance of RKDOSCNV is assessed by comparing it with several current popular methods via experiments with simulated and real data at different tumor purity levels. The experimental results verify that the performance of RKDOSCNV is superior to that of several other methods. In summary, RKDOSCNV is a simple and effective method for the detection of CNVs from whole genome sequencing (WGS) data, especially for samples with low tumor purity.

A Link between Genetic Disorders and Cellular Impairment, Using Human Induced Pluripotent Stem Cells to Reveal the Functional Consequences of Copy Number Variations in the Central Nervous System-A Close Look at Chromosome 15

Recent cutting-edge human genetics technology has allowed us to identify copy number variations (CNVs) and has provided new insights for understanding causative mechanisms of human diseases. A growing number of studies show that CNVs could be associated with physiological mechanisms linked to evolutionary trigger, as well as to the pathogenesis of various diseases, including cancer, autoimmune disease and mental disorders such as autism spectrum disorders, schizophrenia, intellectual disabilities or attention-deficit/hyperactivity disorder. Their incomplete penetrance and variable expressivity make diagnosis difficult and hinder comprehension of the mechanistic bases of these disorders. Additional elements such as co-presence of other CNVs, genomic background and environmental factors are involved in determining the final phenotype associated with a CNV. Genetically engineered animal models are helpful tools for understanding the behavioral consequences of CNVs. However, the genetic background and the biology of these animal model systems have sometimes led to confusing results. New cellular models obtained through somatic cellular reprogramming technology that produce induced pluripotent stem cells (iPSCs) from human subjects are being used to explore the mechanisms involved in the pathogenic consequences of CNVs. Considering the vast quantity of CNVs found in the human genome, we intend to focus on reviewing the current literature on the use of iPSCs carrying CNVs on chromosome 15, highlighting advantages and limits of this system with respect to mouse model systems.

Association of Polyps with Early-Onset Colorectal Cancer and Throughout Surveillance: Novel Clinical and Molecular Implications

Early-onset colorectal cancer (EOCRC) is an increasing and worrisome entity. The aim of this study was to analyze its association with polyps concerning prognosis and surveillance. EOCRC cases were compared regarding the presence or absence of associated polyps (clinical and molecular features), during a minimum of 7 years of follow-up. Of 119 cases, 56 (47%) did not develop polyps (NP group), while 63 (53%) did (P group). The NP group showed a predominant location of the CRC in the rectum (50%), of sporadic cases (54%), and diagnosis at advanced stages: Only P53 and SMARCB1 mutations were statistically linked to this group. The P group, including mainly early-diagnosed tumors, was linked with the most frequent and differential altered chromosomal regions in the array comparative genomic hybridization. The two most frequent groups according to the follow-up were the NP group (40%), and patients developing polyps in the first 5 years of follow-up (P < 5FU) (34%) (these last groups predominantly diagnosed at the earliest stage and with adenomatous polyps (45%)). EOCRC with polyps that developed during the entire follow-up (PDFU group) were mainly located in the right colon (53%), diagnosed in earlier stages, and 75% had a familial history of CRC. Patients developing polyps after the first 5 years (P > 5FU) showed a mucinous component (50%). Our results show that the absence or presence of polyps in EOCRC is an important prognostic factor with differential phenotypes. The development of polyps during surveillance shows that it is necessary to extend the follow-up time, also in those cases with microsatellite-stable EOCRC.

YAP/TAZ Related BioMechano Signal Transduction and Cancer Metastasis

Mechanoreciprocity refers to a cell’s ability to maintain tensional homeostasis in response to various types of forces. Physical forces are continually being exerted upon cells of various tissue types, even those considered static, such as the brain. Through mechanoreceptors, cells sense and subsequently respond to these stimuli. These forces and their respective cellular responses are prevalent in regulating everything from embryogenic tissue-specific differentiation, programmed cell death, and disease progression, the last of which being the subject of extensive attention. Abnormal mechanical remodeling of cells can provide clues as to the pathological status of tissues. This becomes particularly important in cancer cells, where cellular stiffness has been recently accepted as a novel biomarker for cancer metastasis. Several studies have also elucidated the importance of cell stiffness in cancer metastasis, with data highlighting that a reversal of tumor stiffness has the capacity to revert the metastatic properties of cancer. In this review, we summarize our current understanding of extracellular matrix (ECM) homeostasis, which plays a prominent role in tissue mechanics. We also describe pathological disruption of the ECM, and the subsequent implications toward cancer and cancer metastasis. In addition, we highlight the most novel approaches toward understanding the mechanisms which generate pathogenic cell stiffness and provide potential new strategies which have the capacity to advance our understanding of one of human-kinds’ most clinically significant medical pathologies. These new strategies include video-based techniques for structural dynamics, which have shown great potential for identifying full-field, high-resolution modal properties, in this case, as a novel application.

Development of somatic mutation signatures for risk stratification and prognosis in lung and colorectal adenocarcinomas

Background

Prognostic signatures are vital to precision medicine. However, development of somatic mutation prognostic signatures for cancers remains a challenge. In this study we developed a novel method for discovering somatic mutation based prognostic signatures.

Results

Somatic mutation and clinical data for lung adenocarcinoma (LUAD) and colorectal adenocarcinoma (COAD) from The Cancer Genome Atlas (TCGA) were randomly divided into training (n = 328 for LUAD and 286 for COAD) and validation (n = 167 for LUAD and 141 for COAD) datasets. A novel method of using the log2 ratio of the tumor mutation frequency to the paired normal mutation frequency is computed for each patient and missense mutation. The missense mutation ratios were mean aggregated into gene-level somatic mutation profiles. The somatic mutations were assessed using univariate Cox analysis on the LUAD and COAD training sets separately. Stepwise multivariate Cox analysis resulted in a final gene prognostic signature for LUAD and COAD. Performance was compared to gene prognostic signatures generated using the same pipeline but with different somatic mutation profile representations based on tumor mutation frequency, binary calls, and gene-gene network normalization. Signature high-risk LUAD and COAD cases had worse overall survival compared to the signature low-risk cases in the validation set (log-rank test p-value = 0.0101 for LUAD and 0.0314 for COAD) using mutation tumor frequency ratio (MFR) profiles, while all other methods, including gene-gene network normalization, have statistically insignificant stratification (log-rank test p-value ≥0.05). Most of the genes in the final gene signatures using MFR profiles are cancer-related based on network and literature analysis.

Conclusions

We demonstrated the robustness of MFR profiles and its potential to be a powerful prognostic tool in cancer. The results are robust according to validation testing and the selected genes are biologically relevant.