Integrated analysis of homozygous deletions, focal amplifications, and sequence alterations in breast and colorectal cancers

Efficient and accurate framework for genome-wide gene-environment interaction analysis in large-scale biobanks

Gene-environment interaction (G×E) analysis elucidates the interplay between genetic and environmental factors. Genome-wide association studies (GWAS) have expanded to encompass complex traits like time-to-event and ordinal traits, which provide richer phenotypic information. However, most existing scalable approaches focus only on quantitative or binary traits. Here we propose SPAGxECCT, a scalable and accurate framework for diverse trait types. SPAGxECCT fits a genotype-independent model and employs a hybrid strategy including saddlepoint approximation (SPA) for accurate p value calculation, especially for low-frequency variants and unbalanced phenotypic distributions. We extend SPAGxECCT to SPAGxEmixCCT, which accounts for population stratification and is applicable to multi-ancestry or admixed populations. SPAGxEmixCCT can further be extended to SPAGxEmixCCT-local, which identifies ancestry-specific G×E effects using local ancestry. Through extensive simulations and real data analyses of UK Biobank data, we demonstrate that SPAGxECCT and SPAGxEmixCCT are scalable to analyze large-scale study cohort, control type I error rates effectively, and maintain power.

Downregulation of solute carrier family 4 members 4 as a biomarker for colorectal cancer

Colorectal cancer (CRC) is one of the major cancer types associated with increased mortality worldwide. Hence, identifying reliable biomarkers make it very essential for early diagnosis and prognosis of CRC. Numerous studies have been conducted to decipher molecular mechanisms underlying CRC, however more deep insightful knowledge is the need of the hour. The purpose of this study was to identify promising key candidate genes in colorectal cancer (CRC) and assess their expression and clinical significance. To clarify and verify promising key biomarkers with signal transduction pathways in colorectal cancer, we integrated 11 microarray datasets from NCBI-GEO. This study utilized multiple bioinformatics tools and databases, including OncoDB, GEO2R, UALCAN, GEIPA, TIMER, and DAVID. The gene expression profiles of eleven datasets (GSE10714, GSE113513, GSE13471, GSE15960, GSE24514, GSE32323, GSE41258, GSE4183, GSE44076, GSE44861, GSE9348) were screened. In 11 gene expression profiles, 3 downregulated genes were identified and validated by databases such as OncoDB, UALCAN, GEIPA and TIMER. Downregulation of SLC4A4 with significant predictive value was validated by multi-omic data analysis and validated by Gene Expression Omnibus (GEO). GEIPA survival analysis showed that low SLC4A4 expression correlated with poorer overall survival among CRC patients. Based on this study, we identified SLC4A4 as a potential candidate biomarker for colorectal cancer (CRC), enabling early diagnosis and prognosis with molecular targeted therapy.

Replication stress increases de novo CNVs across the malaria parasite genome

Changes in the copy number of large genomic regions, termed copy number variations (CNVs), contribute to important phenotypes in many organisms. CNVs are readily identified using conventional approaches when present in a large fraction of the cell population. However, CNVs that are present in only a few genomes across a population are often overlooked but important; if beneficial under specific conditions, a de novo CNV that arises in a single genome can expand during selection to create a larger population of cells with novel characteristics. While the reach of single cell methods to study de novo CNVs is increasing, we continue to lack information about CNV dynamics in rapidly evolving microbial populations. Here, we investigated de novo CNVs in the genome of the Plasmodium parasite that causes human malaria. The highly AT-rich P. falciparum genome readily accumulates CNVs that facilitate rapid adaptation to new drugs and host environments. We employed a low-input genomics approach optimized for this unique genome as well as specialized computational tools to evaluate the de novo CNV rate both before and after the application of stress. We observed a significant increase in genomewide de novo CNVs following treatment with a replication inhibitor. These stress-induced de novo CNVs encompassed genes that contribute to various cellular pathways and tended to be altered in clinical parasite genomes. This snapshot of CNV dynamics emphasizes the connection between replication stress, DNA repair, and CNV generation in this important microbial pathogen.

Molecular pathogenesis of microsatellite instability-high early-stage colorectal adenocarcinoma in India

OBJECTIVES

The prevalence of microsatellite instability (MSI) subtype among all colon cancers in India is about 30 %, approximately two times more than that of western population suggesting different molecular pathogeneses.

METHODS

A NanoString analysis-based Pan cancer differential expression (DE) profile was determined in a primary cohort of early-stage CRC (tumor=10, normal=7), and correlated against MSI status. Using RT-PCR, tumor-specific DE genes were validated in another cohort of MSI-high CRC (n=15).

RESULTS

Among the most differentially expressed genes, AXIN2, ETV4, and RNF43 were tumor cell-specific signals, while a set of genes including COL11A1, COMP, INHBA, SPP1, MMP3, TLR2, and others were immune cell-specific signals, that had a differential expression between MSI and MSS groups. When overlapped with The Cancer Genome Atlas (TCGA) studies using the Tumor immune estimation resource tool (TIMER), and protein-protein interaction analysis by STRING.db, these genes were segregated to representative tumor cells and immune cells. On validation, the tumor-specific gene signals were inversely associated with TLR4 expression.

CONCLUSIONS

The differential expression distribution of AXIN2, ETV4, and RNF43 among tumor and immune cells, suggests more than one pathological subset in the MSI-H subgroup of early-stage CRC in the Indian population.

Mitochondrial metallopeptidase OMA1 in cancer

Our understanding of the roles that mitochondria play in cellular physiology has evolved drastically-from a mere cellular energy supplier to a crucial regulator of metabolic and signaling processes, particularly in the context of development and progression of human diseases such as cancers. The present review examines the role of OMA1, a conserved, redox-sensitive metallopeptidase in cancer biology. OMA1's involvement in mitochondrial quality control, redox activity, and stress responses underscores its potential as a novel target in cancer diagnosis and treatment. However, our incomplete understanding of OMA1's regulation and structural detail presents ongoing challenges to target OMA1 for therapeutic purposes. Further exploration of OMA1 holds promise in uncovering novel insights into cancer mechanisms and therapeutic strategies. In this chapter, we briefly summarize our current knowledge about OMA1, its redox-regulation, and emerging role in certain cancers.

Genomic landscape of diploid and aneuploid microsatellite stable early onset colorectal cancer

Although colorectal cancer (CRC) remains the second leading cause of cancer-related death in the United States, the overall incidence and mortality from the disease have declined in recent decades. In contrast, there has been a steady increase in the incidence of CRC in individuals under 50 years of age. Hereditary syndromes contribute disproportionately to early onset CRC (EOCRC). These include microsatellite instability high (MSI+) tumors arising in patients with Lynch Syndrome. However, most EOCRCs are not associated with familial syndromes or MSI+ genotypes. Comprehensive genomic profiling has provided the basis of improved more personalized treatments for older CRC patients. However, less is known about the basis of sporadic EOCRC. To define the genomic landscape of EOCRC we used DNA content flow sorting to isolate diploid and aneuploid tumor fractions from 21 non-hereditary cases. We then generated whole exome mutational profiles for each case and whole genome copy number, telomere length, and EGFR immunohistochemistry (IHC) analyses on subsets of samples. These results discriminate the molecular features of diploid and aneuploid EOCRC and provide a basis for larger population-based studies and the development of effective strategies to monitor and treat this emerging disease.

CDCA8, a mitosis-related gene, as a prospective pan-cancer biomarker: implications for survival prognosis and oncogenic immunology

BACKGROUND

Human cell division cycle-associated protein 8 (CDCA8), a critical regulator of mitosis, has been identified as a prospective prognostic biomarker in several cancer types, including breast, colon, and lung cancers. This study analyzed the diagnostic/prognostic potential and clinical implications of CDCA8 across diverse cancers.

METHODS

Bioinformatics and molecular experiments.

RESULTS

Analyzing TCGA data via TIMER2 and GEPIA2 databases revealed significant up-regulation of CDCA8 in 23 cancer types compared to normal tissues. Prognostically, elevated CDCA8 expression correlated with poorer overall survival in KIRC, LUAD, and SKCM, emphasizing its potential as a prognostic marker. UALCAN analysis demonstrated CDCA8 up-regulation based on clinical variables, such as cancer stage, race, and gender, in these cancers. Epigenetic exploration indicated reduced CDCA8 promoter methylation levels in Kidney Renal Clear Cell Carcinoma (KIRC), Lung Adenocarcinoma (LUAD), and Skin Cutaneous Melanoma (SKCM) tissues compared to normal controls. Promoter methylation and mutational analyses showcased a hypomethylation and low mutation rate for CDCA8 in these cancers. Correlation analysis revealed positive associations between CDCA8 expression and infiltrating immune cells, particularly CD8+ and CD4+ T cells. Protein-protein interaction (PPI) network analysis unveiled key interacting proteins, while gene enrichment analysis highlighted their involvement in crucial cellular processes and pathways. Additionally, exploration of CDCA8-associated drugs through DrugBank presented potential therapeutic options for KIRC, LUAD, and SKCM. In vitro validation using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) confirmed elevated CDCA8 expression in LUAD cell lines (A549 and H1299) compared to control cell lines (Beas-2B and NL-20).

CONCLUSION

This study provides concise insights into CDCA8's multifaceted role in KIRC, LUAD, and SKCM, covering expression patterns, diagnostic and prognostic relevance, epigenetic regulation, mutational landscape, immune infiltration, and therapeutic implications.

Tracing back primed resistance in cancer via sister cells

Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. Here, we present ReSisTrace that uses shared transcriptomic features of sister cells to predict the states priming treatment resistance. Applying ReSisTrace in ovarian cancer cells perturbed with olaparib, carboplatin or natural killer (NK) cells reveals pre-resistant phenotypes defined by proteostatic and mRNA surveillance features, reflecting traits enriched in the upcoming subclonal selection. Furthermore, we show that DNA repair deficiency renders cells susceptible to both DNA damaging agents and NK killing in a context-dependent manner. Finally, we leverage the obtained pre-resistance profiles to predict and validate small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification and discovery of synergistic pre-sensitizing therapies.

Multiple Protein Biomarkers and Different Treatment Strategies for Colorectal Carcinoma: A Comprehensive Prospective

In this review, we emphasized important biomarkers, pathogenesis, and newly developed therapeutic approaches in the treatment of colorectal cancer (CRC). This includes a complete description of small-molecule inhibitors, phytopharmaceuticals with antiproliferative potential, monoclonal antibodies for targeted therapy, vaccinations as immunotherapeutic agents, and many innovative strategies to intervene in the interaction of oncogenic proteins. Many factors combine to determine the clinical behavior of colorectal cancer and it is still difficult to comprehend the molecular causes of a person's vulnerability to CRC. It is also challenging to identify the causes of the tumor's onset, progression, and responsiveness or resistance to antitumor treatment. Current recommendations for targeted medications are being updated by guidelines throughout the world in light of the growing number of high-quality clinical studies. So, being concerned about the aforementioned aspects, we have tried to present a summarized pathogenic view, including a brief description of biomarkers and an update of compounds with their underlying mechanisms that are currently under various stages of clinical testing. This will help to identify gaps or shortfalls that can be addressed in upcoming colorectal cancer research.

DNA Copy Number Alterations and Copy Neutral Loss of Heterozygosity in Adult Ph-Negative Acute B-Lymphoblastic Leukemia: Focus on the Genes Involved

The landscape of chromosomal aberrations in the tumor cells of the patients with B-ALL is diverse and can influence the outcome of the disease. Molecular karyotyping at the onset of the disease using chromosomal microarray (CMA) is advisable to identify additional molecular factors associated with the prognosis of the disease. Molecular karyotyping data for 36 patients with Ph-negative B-ALL who received therapy according to the ALL-2016 protocol are presented. We analyzed copy number alterations and their prognostic significance for CDKN2A/B, DMRTA, DOCK8, TP53, SMARCA2, PAX5, XPA, FOXE1, HEMGN, USP45, RUNX1, NF1, IGF2BP1, ERG, TMPRSS2, CRLF2, FGFR3, FLNB, IKZF1, RUNX2, ARID1B, CIP2A, PIK3CA, ATM, RB1, BIRC3, MYC, IKZF3, ETV6, ZNF384, PTPRJ, CCL20, PAX3, MTCH2, TCF3, IKZF2, BTG1, BTG2, RAG1, RAG2, ELK3, SH2B3, EP300, MAP2K2, EBI3, MEF2D, MEF2C, CEBPA, and TBLXR1 genes, choosing t(4;11) and t(7;14) as reference events. Of the 36 patients, only 5 (13.8%) had a normal molecular karyotype, and 31 (86.2%) were found to have various molecular karyotype abnormalities-104 deletions, 90 duplications or amplifications, 29 cases of cnLOH and 7 biallelic/homozygous deletions. We found that 11q22-23 duplication involving the BIRC3, ATM and MLL genes was the most adverse prognostic event in the study cohort.

The Impact of BRAF Mutation Status on Survival Outcomes and Treatment Patterns among Metastatic Colorectal Cancer Patients in Alberta, Canada

Colorectal cancer presents via multiple different clinical phenotypes that can arise from a variety of different genetic and molecular alterations. The aim of this study was to describe survival outcomes and treatment patterns of metastatic colorectal cancer (mCRC) patients by v-raf murine sarcoma viral oncogene homolog B1 (BRAF) mutation status. The Alberta Cancer Registry was used to identify all patients >18 years old who had been diagnosed with mCRC in Alberta between 1 January 2017 and 31 December 2019 and had received at least one cycle of systemic therapy. Treatment patterns were compared between wild-type and mutant BRAF mCRC patients. Cox regression models and Kaplan-Meier curves were created to assess survival differences by both treatment pattern and BRAF status. A total of 488 patients were identified with mCRC, of which 42 (11.4%) were confirmed to have a BRAF mutation. The most common first-line treatment regimen was either capecitabine and oxaliplatin (CAPOX) or leucovorin calcium (folinic acid), fluorouracil, and oxaliplatin (FOLFOX). The median overall survival for mCRC patients was 20.01 months. Mutant BRAF patients had a median survival of 8.21 months compared to 20.03 months among those with wild-type BRAF. BRAF mutations among mCRC patients are associated with a considerably poor prognosis, reinforcing the need for clinical BRAF testing among newly diagnosed patients to better understand their prognosis.

In silico analysis of differentially expressed-aberrantly methylated genes in breast cancer for prognostic and therapeutic targets

Breast cancer (BC) is the leading cause of death among women across the globe. Abnormal gene expression plays a crucial role in tumour progression, carcinogenesis and metastasis of BC. The alteration of gene expression may be through aberrant gene methylation. In the present study, differentially expressed genes which may be regulated by DNA methylation and their pathways associated with BC have been identified. Expression microarray datasets GSE10780, GSE10797, GSE21422, GSE42568, GSE61304, GSE61724 and one DNA methylation profile dataset GSE20713 were downloaded from Gene Expression Omnibus database (GEO). Differentially expressed-aberrantly methylated genes were identified using online Venn diagram tool. Based on fold change expression of differentially expressed-aberrantly methylated genes were chosen through heat map. Protein-protein interaction (PPI) network of the hub genes was constructed by Search Tool for the Retrieval of Interacting Genes (STRING). Gene expression and DNA methylation level of the hub genes were validated through UALCAN. Overall survival analysis of the hub genes was analysed through Kaplan-Meier plotter database for BC. A total of 72 upregulated-hypomethylated genes and 92 downregulated-hypermethylated genes were obtained from GSE10780, GSE10797, GSE21422, GSE42568, GSE61304, GSE61724, and GSE20713 datasets by GEO2R and Venn diagram tool. PPI network of the upregulated-hypomethylated hub genes (MRGBP, MANF, ARF3, HIST1H3D, GSK3B, HJURP, GPSM2, MATN3, KDELR2, CEP55, GSPT1, COL11A1, and COL1A1) and downregulated-hypermethylated hub genes were constructed (APOD, DMD, RBPMS, NR3C2, HOXA9, AMKY2, KCTD9, and EDN1). All the differentially expressed hub genes expression was validated in UALCAN database. 4 in 13 upregulated-hypomethylated and 5 in 8 downregulated-hypermethylated hub genes to be significantly hypomethylated or hypermethylated in BC were confirmed using UALCAN database (p < 0.05). MANF, HIST1H3D, HJURP, GSK3B, GPSM2, MATN3, KDELR2, CEP55, COL1A1, APOD, RBPMS, NR3C2, HOXA9, ANKMY2, and EDN1 were significantly (p < 0.05) associated with poor overall survival (OS). The identified aberrantly methylated-differentially expressed genes and their related pathways and function in BC can serve as novel diagnostic and prognostic biomarkers and therapeutic targets.Please confirm if the author names are presented accurately and in the correct sequence (given name, middle name/initial, family name). Author 4 Given name: [Jeewan Ram] Last name [Vishnoi]. Also, kindly confirm the details in the metadata are correct.It is correct.

Persistent mutation burden drives sustained anti-tumor immune responses

Tumor mutation burden is an imperfect proxy of tumor foreignness and has therefore failed to consistently demonstrate clinical utility in predicting responses in the context of immunotherapy. We evaluated mutations in regions of the genome that are unlikely to undergo loss in a pan-cancer analysis across 31 tumor types (n = 9,242) and eight immunotherapy-treated cohorts of patients with non-small-cell lung cancer, melanoma, mesothelioma, and head and neck cancer (n = 524). We discovered that mutations in single-copy regions and those present in multiple copies per cell constitute a persistent tumor mutation burden (pTMB) which is linked with therapeutic response to immune checkpoint blockade. Persistent mutations were retained in the context of tumor evolution under selective pressure of immunotherapy and tumors with a high pTMB content were characterized by a more inflamed tumor microenvironment. pTMB imposes an evolutionary bottleneck that cancer cells cannot overcome and may thus drive sustained immunologic tumor control in the context of immunotherapy.

High concordance rate of capillary electrophoresis workflow for microsatellite instability analysis and mismatch repair (MMR) immunostaining in colorectal carcinoma

Microsatellite instability (MSI) is the primary predictive biomarker for therapeutic efficacies of cancer immunotherapies. Establishment of the MSI detection methods with high sensitivity and accessibility is important. Because MSI is mainly caused by defects in DNA mismatch repair (MMR), immunohistochemical (IHC) staining for the MMR proteins has been widely employed to predict the responses to immunotherapies. Thus, due to the high sensitivity of PCR, the MSI-PCR analysis has also been recommended as the primary approach as MMR IHC. This study aimed to develop a sensitive and convenient platform for daily MSI-PCR services. The routine workflow used a non-labeling QIAxcel capillary electrophoresis system which did not need the fluorescence labeling of the DNA products or usage of a multi-color fluorescence reader. Furthermore, the 15 and 1000 bp size alignment markers were used to precisely detect the size of the DNA product. A cohort of 336 CRC cases was examined by MSI-PCR on the five mononucleotide MSI markers recommended by ESMO. The PCR products were analyzed in the screening gels, followed by high-resolution gel electrophoresis for confirmation if needed. In the MSI-PCR tests, 90.1% (303/336) cases showed clear major shift patterns in the screening gels, and only 33 cases had to be re-examined using the high-resolution gels. The cohort was also analyzed by MMR IHC is, which revealed 98.5% (331/336) concordance with MSI-PCR. In the five discordant cases, 4 (3 MSI-L and 1 MSS) showed MSH6 loss. Besides, one case exhibited MSI-H but no loss in the MMR IHC. Further NGS analysis, in this case, found that missense and frameshift mutations in the PMS2 and MSH6 genes occurred, respectively. In conclusion, the non-labeling MSI-PCR capillary electrophoresis revealed high concordance with the MMR IHC analysis and is cost- and time-effective. Therefore, it shall be highly applicable in clinical laboratories.

Heat selection enables highly scalable methylome profiling in cell-free DNA for noninvasive monitoring of cancer patients

Genome-wide analysis of cell-free DNA methylation profile is a promising approach for sensitive and specific detection of many cancers. However, scaling such assays for clinical translation is impractical because of the high cost of whole-genome bisulfite sequencing. We show that the small fraction of GC-rich genome is highly enriched in CpG sites and disproportionately harbors most of the cancer-specific methylation signature. Here, we report on the simple and effective heat enrichment of CpG-rich regions for bisulfite sequencing (Heatrich-BS) platform that allows for focused methylation profiling in these highly informative regions. Our novel method and bioinformatics algorithm enable accurate tumor burden estimation and quantitative tracking of colorectal cancer patient's response to treatment at much reduced sequencing cost suitable for frequent monitoring. We also show tumor epigenetic subtyping using Heatrich-BS, which could enable patient stratification. Heatrich-BS holds great potential for highly scalable screening and monitoring of cancer using liquid biopsy.

Responses to the Tepotinib in Gastric Cancers with MET Amplification or MET Exon 14 Skipping Mutations and High Expression of Both PD-L1 and CD44

Both MET exon 14 skipping mutation (METex14SM) and high copy-number variation (CNV) lead to enhanced carcinogenesis; additionally, programmed-death ligand 1 (PD-L1) is often upregulated in cancers. In this study, we characterized the expression of MET (including METex14SM), PD-L1, and CD44 in human gastric cancer (GC) cells as well as the differential susceptibility of these cells to tepotinib. Tepotinib treatments inhibited the growth of five GC cells in a dose-dependent manner with a concomitant induction of cell death. Tepotinib treatments also significantly reduced the expression of phospho-MET, total MET, c-Myc, VEGFR2, and Snail protein in SNU620, MKN45, and Hs746T cells. Notably, tepotinib significantly reduced the expression of CD44 and PD-L1 in METex14SM Hs746T cells. By contrast, tepotinib was only slightly active against SNU638 and KATO III cells. Migration was reduced to a greater extent in the tepotinib-treated group than in the control group. Tepotinib may have therapeutic effects on c-MET-amplified GC, a high expression of both PD-L1 and CD44, and METex14SM. Clinical studies are needed to confirm these therapeutic effects.

Relationship Between CNVs and Immune Cells Infiltration in Gastric Tumor Microenvironment

Gastric cancer (GC) is a highly fatal and common malignancy of the digestive system. Recent therapeutic advancements have significantly improved the clinical outcomes in GC, but due to the unavailability of suitable molecular targets, a large number of patients do not respond to the immune checkpoint inhibitors (ICI) therapy. To identify and validate potential therapeutic and prognostic targets of gastric cancer, we used the “inferCNV” R package for analyzing single-cell sequencing data (GSE112302) of GC and normal epithelial cells. First, by using LASSO, we screened genes that were highly correlated with copy number variations (CNVs). Therefrom, five gene signature (CPVL, DDC, GRTP1, ONECUT2, and PRSS21) was selected by cross-validating the prognosis and risk management with the GC RNA-seq data obtained from GEO and TCGA. Moreover, the correlation analyses between CNVs of these genes and immune cell infiltration in gastric cancer identified CPVL as a potential prognostic marker. Finally, CPVL showed high expression in gastric cancer samples and cell lines, then siRNA-mediated silencing of CPVL expression in gastric cancer cells showed significant proliferation arrest in MGC803 cells. Here, we conclude that CNVs are key regulators of the immune cells infiltration in gastric TME as well as cancer development, and CPVL could potentially be used as a prognostic and therapeutic marker in gastric cancer.

GenomeTornadoPlot: a novel R package for CNV visualization and focality analysis

MOTIVATION

Analysis of focal copy number variations (CNVs) is highly relevant for cancer research, as they pinpoint driver genes. More specifically, due to selective pressure oncogenes and tumor suppressor genes are more often affected by these events than neighboring passengers. In cases where multiple candidates co-reside in a genomic locus, careful comparison is required to either identify multigenic minimally deleted regions of synergistic co-mutations, or the true single driver gene. The study of focal CNVs in large cancer genome cohorts requires specialized visualization and statistical analysis.

RESULTS

We developed the GenomeTornadoPlot R-package which generates gene-centric visualizations of CNV types, locations and lengths from cohortwise NGS data. Furthermore, the software enables the pairwise comparison of proximate genes to identify co-mutation patterns or driver-passenger hierarchies. The visual examination provided by GenomeTornadoPlot is further supported by adaptable local and global focality scoring. Integrated into the GenomeTornadoPlot R-Package is the comprehensive PCAWG database of CNVs, comprising 2976 cancer genome entities from 46 cohorts of the Pan-cancer Analysis of Whole Genomes project. The GenomeTornadoPlot R-package can be used to perform exploratory or hypothesis-driven analyses on the basis of the PCAWG data or in combination with data provided by the user.

AVAILABILITY AND IMPLEMENTATION

GenomeTornadoPlot is written in R script and released via github: <https://github.com/chenhong-dkfz/GenomeTornadoPlot/>. The package is under the license of GPL-3.0.

The emerging roles of NGS in clinical oncology and personalized medicine

Next-generation sequencing (NGS) has been increasingly popular in genomics studies over the last decade, as new sequencing technology has been created and improved. Recently, NGS started to be used in clinical oncology to improve cancer therapy through diverse modalities ranging from finding novel and rare cancer mutations, discovering cancer mutation carriers to reaching specific therapeutic approaches known as personalized medicine (PM). PM has the potential to minimize medical expenses by shifting the current traditional medical approach of treating cancer and other diseases to an individualized preventive and predictive approach. Currently, NGS can speed up in the early diagnosis of diseases and discover pharmacogenetic markers that help in personalizing therapies. Despite the tremendous growth in our understanding of genetics, NGS holds the added advantage of providing more comprehensive picture of cancer landscape and uncovering cancer development pathways. In this review, we provided a complete overview of potential NGS applications in scientific and clinical oncology, with a particular emphasis on pharmacogenomics in the direction of precision medicine treatment options.

Obesity and Inflammation: Colorectal Cancer Engines

The prevalence of obesity continues to increase to the extent that it became a worldwide pandemic. An accumulating body of evidence has associated obesity with the development of different types of cancer, including colorectal cancer, which is a notorious disease with a high mortality rate. At the molecular level, colorectal cancer is a heterogenous disease characterized by a myriad of genetic and epigenetic alterations associated with various forms of genomic instability (detailed in Supplementary Materials). Recently, the microenvironment has emerged as a major factor in carcinogenesis. Our aim is to define the different molecular alterations leading to the development of colorectal cancer in obese patients with a focus on the role of the microenvironment in carcinogenesis. We also highlight all existent molecules in clinical trials that target the activated pathways in obesity-associated colorectal cancer, whether used as single treatments or in combination. Obesity predisposes to colorectal cancer via creating a state of chronic inflammation with dysregulated adipokines, inflammatory mediators, and other factors such as immune cell infiltration. A unifying theme in obesity-mediated colorectal cancer is the activation of the PI3K/AKT, mTOR/MAPK, and STAT3 signaling pathways. Different inhibitory molecules towards these pathways exist, increasing the therapeutic choice of obesity-associated colon cancer. However, obese patients are more likely to suffer from chemotherapy overdosing. Preventing obesity through maintaining a healthy and active lifestyle remains to be the best remedy.

Discovery of a novel and a rare Kristen rat sarcoma viral oncogene homolog (KRAS) gene mutation in colorectal cancer patients

Colorectal cancer (CRC) is one of the most important causes of morbidity and mortality in the developed world and is gradually more frequent in the developing world including Saudi Arabia. According to the Saudi Cancer Registry report 2015, CRC is the most common cancer in men (14.9%) and the second most prevalent cancer. Oncogenic mutations in the KRAS gene play a central role in tumorigenesis and are mutated in 30-40% of all CRC patients. To explore the prevalence of KRAS gene mutations in the Saudi population, we collected 80 CRC tumor tissues and sequenced the KRAS gene using automated sequencing technologies. The chromatograms presented mutations in 26 patients (32.5%) in four different codons, that is, 12, 13, 17, and 31. Most of the mutations were identified in codon 12 in 16 patients (61.5% of all mutations). We identified a novel mutation c.51 G>A in codon 17, where serine was substituted by arginine (S17R) in four patients. We also identified a very rare mutation, c.91 G>A, in which glutamic acid was replaced by lysine (E31K) in three patients. In conclusion, our findings further the knowledge about KRAS mutations in different ethnic groups is indispensable to fully understand their role in the development and progression of CRC.

Pilot Nanostring PanCancer pathway analysis of colon adenocarcinoma in a tertiary healthcare centre in Kerala, India

The prevalence of microsatellite instability and deoxyribonucleic acid mismatch repair deficiency in colorectal adenocarcinoma (CRC) cases is higher in India compared to western populations. No major study on the molecular pathogenesis is currently available in the Indian population. We conducted a pilot study to explore the differences in molecular pathogenesis of microsatellite stable (MSS) and microsatellite unstable CRC from a tertiary care centre in Kerala, South India. Using Nanostring PanCancer panel assay in Stage II colorectal adenocarcinoma, tumour tissues (n = 11) were compared against normal colon tissues (n = 4). Differentially expressed (DE) genes were identified and super-imposed onto colon adenocarcinoma cohort of The Cancer Genome Atlas (TCGA) data (TCGA Colon Adenocarcinoma (TCGA COAD)), from the Genome Expression Profiling Interactive Analysis and Tumor Immune Estimation Resource (TIMER) to compare the gene associations. Significant DE genes were 59 out of 730 (false discovery rate adj. p-value < 0.05), 18 of which had a fold-change |FC(log2)| ≥ 2. On superimposition to TCGA COAD, 33 genes were significant in both TCGA and current study. ETV4 was expressed significantly higher in MSS with no immune cell infiltration. Other significant DE genes with high FC(log2), unique to the study were INHBA, COL1A1, COL11A1, COMP, SFRP4 and SPP1, which were clustered in STRING network analysis and correlated with tumour-infiltrating immune cells in TIMER, suggesting a specific interaction pathway. The preliminary study suggests a distinct pathogenesis of MSS CRC involving ETV4 in the Indian population and warrants further clinically extensive and high-dimensional expression studies.

Pan-cancer analysis of the oncogenic role of discs large homolog associated protein 5 (DLGAP5) in human tumors

BACKGROUND

In recent years, there have been many studies on the relationship between DLGAP5 and different types of cancers, yet there is no pan-cancer analysis of DLGAP5. Therefore, this study aims to analyze the roles of DLGAP5 in human tumors.

METHODS

Firstly, we evaluated the expression level of DLGAP5 in 33 types of tumors throughout the datasets of TCGA (Cancer Genome Atlas) and GEO (Gene Expression Synthesis). Secondly, we used the GEPIA2 and Kaplan-Meier plotter to conduct Survival prognosis analysis. Additionally, cBioPortal web was utilized to analyze the genetic alteration of DLGAP5, after which we selected hepatocellular carcinoma (HCC) cell lines to define the function of DLGAP5. Last but not least, we performed immune infiltration analysis and DLGAP5-related gene enrichment analysis.

RESULTS

DLGAP5 is highly expressed in most type of cancers, and there is a significant correlation between the expression of DLGAP5 and the prognosis of cancer patients. We have observed that DLGAP5 promotes the proliferation and invasion of hepatocellular carcinoma (HCC) cell lines. We also found that DLGAP5 expression was related with the CD8⁺ T-cell infiltration status in kidney renal clear cell carcinoma, uveal melanoma, and thymoma, and cancer-associated fibroblast infiltration was observed in breast invasive carcinoma, kidney renal papillary cell carcinoma and testicular germ cell tumors. In addition, enrichment analysis revealed that cell cycle- and oocyte meiosis-associated functions were involved in the functional mechanism of DLGAP5.

CONCLUSIONS

Taken together, our unpresented pan-cancer analysis of DLGAP5 provides a relatively integrative understanding of the oncogenic role of DLGAP5 in various tumors. DLGAP5 may prompt HCC cellular proliferation, invasion and metastasis. All of these provides solid basement and will promote more advanced understanding the role of DLGAP5 in tumorigenesis and development from the perspective of clinical tumor samples and cells.

Whole-exome sequencing of alpha-fetoprotein producing gastric carcinoma reveals genomic profile and therapeutic targets

Alpha-fetoprotein producing gastric carcinoma (AFPGC) is a rare and aggressive subtype of gastric cancer. However, little is known about the genomic features of this disease. We perform whole-exome sequencing analysis of AFPGC, and identify 34 significantly mutated genes. Somatic copy number alterations analysis reveals several significant focal amplifications (e.g. 19q12, 17q12) and focal deletions (e.g. 1p36.11, 9p21.3), and some of these negatively affect the patient prognosis. Comparative analyses reveal that AFPGC has distinct genomic features from gastric cancer of The Cancer Genome Atlas as well as four molecular subtypes. Several frequently altered genes with potential as therapeutic targets are identified in AFPGC. Further analysis reveals that AFPGC with amplification of CCNE1 at 19q12 and/or ERBB2 at 17q12 show poorer survival and more aggressive. Subsequently, based on our established patient-derived xenograft models for AFPGC, translational research is performed and the therapeutic value of targeting CCNE1 and ERBB2 is validated. In this work, we provide an understanding of genomic characteristics of AFPGC and propose a platform to explore and validate the genome-guided personalized treatment for this disease.

Molecular subtypes of colorectal cancer: An emerging therapeutic opportunity for personalized medicine

Molecular subtypes-based therapies offer new potential framework for desired and precise outcome in clinical settings. Current treatment strategies in colorectal cancer are largely 'one drug fit all' model for patients that display same pathological conditions. However, CRC is a very heterogenous set of malignancy that does not support for above criteria. Each subtype displays different pathological and genetic signatures. Based on these features, therapeutic stratification for individual patients may be designed, which may ultimately lead to improved therapeutic outcomes. In this comprehensive review, we have attempted to briefly outline major CRC pathways. A detailed overview of molecular subtypes and their clinical significance has been discussed. Present and future methods, governing CRC subtyping in the era of personalized therapy with a special emphasis on CMS subtypes of CRC has been reviewed. Together, discovery and validation of new CRC patient stratification methods, screening for novel therapeutic targets, and enhanced diagnosis of CRC may improve the treatment outcome.

Quantitative evaluation of PTPN22 copy number variation by digital droplet PCR and association with type 2 diabetes risk

Type 2 diabetes (T2D) is a chronic endocrine disorder with rapidly increasing prevalence worldwide. Genetic instability leading to metabolic dysfunction plays an important role in T2D susceptibility and progression. Structural alteration in genome, that is, copy number variation (CNV) is emerging as the inherent marker for disease identification. Previous genomic CNV array revealed that protein tyrosine phosphatase non-receptor type 22 (PTPN22) gene was overlapped with a CNV region, however, whether this CNV affected T2D risk remains to be further elucidated. In this study, we first identified divergent distributions of the PTPN22 copy number (CN) between T2D patients and healthy controls in Chinese population (p < 0.01). Risk assessment analysis revealed that the CN gain (OR = 3.28, p < 0.001) was the promising risk factor for T2D. Also, significantly positive correlations of the PTPN22 CNV with fasting plasma glucose and glycated hemoglobin were demonstrated in T2D patients. Statistical association analysis investigated that the T2D individuals carrying CN gain showed higher plasma glucose and lower insulin levels than those carrying CN normal and loss at 60 min/120 min/180 min during an OGTT test. In addition, the PTPN22 CNV had an effect on total cholesterol, and the CN gain presented higher values than the other two CN types. These results suggested that the CN gain types of the PTPN22 gene accompany with the glycometabolism dysregulation, and finally predispose their carriers to T2D; therefore, the PTPN22 CNV may be a promising biomarker for predicting T2D risk, or a clinical target for T2D diagnosis and therapy.

Copy number variation: Characteristics, evolutionary and pathological aspects

Copy number variants (CNVs) were the subject of extensive research in the past years. They are common features of the human genome that play an important role in evolution, contribute to population diversity, development of certain diseases, and influence host–microbiome interactions. CNVs have found application in the molecular diagnosis of many diseases and in non-invasive prenatal care, but their full potential is only emerging. CNVs are expected to have a tremendous impact on screening, diagnosis, prognosis, and monitoring of several disorders, including cancer and cardiovascular disease. Here, we comprehensively review basic definitions of the term CNV, outline mechanisms and factors involved in CNV formation, and discuss their evolutionary and pathological aspects. We suggest a need for better defined distinguishing criteria and boundaries between known types of CNVs.

Bea A.58de JongSteven58KralovaPetra59SedlacekRadislav59ClaeysElisa60LeucciEleonora60BorsaniMassimiliano61LanfranconeLuisa61PelicciPier Giuseppe61MælandsmoGunhild Mari62NorumJens Henrik62VinoloEmilie63. Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

Molecular Mechanisms of Colon Cancer Progression and Metastasis: Recent Insights and Advancements

Colorectal cancer (CRC), the third most common type of cancer, is the second leading cause of cancer-related mortality rates worldwide. Although modern research was able to shed light on the pathogenesis of CRC and provide enhanced screening strategies, the prevalence of CRC is still on the rise. Studies showed several cellular signaling pathways dysregulated in CRC, leading to the onset of malignant phenotypes. Therefore, analyzing signaling pathways involved in CRC metastasis is necessary to elucidate the underlying mechanism of CRC progression and pharmacotherapy. This review focused on target genes as well as various cellular signaling pathways including Wnt/β-catenin, p53, TGF-β/SMAD, NF-κB, Notch, VEGF, and JAKs/STAT3, which are associated with CRC progression and metastasis. Additionally, alternations in methylation patterns in relation with signaling pathways involved in regulating various cellular mechanisms such as cell cycle, transcription, apoptosis, and angiogenesis as well as invasion and metastasis were also reviewed. To date, understanding the genomic and epigenomic instability has identified candidate biomarkers that are validated for routine clinical use in CRC management. Nevertheless, better understanding of the onset and progression of CRC can aid in the development of early detection molecular markers and risk stratification methods to improve the clinical care of CRC patients.

Identification of relevant genetic alterations in cancer using topological data analysis

Large-scale cancer genomic studies enable the systematic identification of mutations that lead to the genesis and progression of tumors, uncovering the underlying molecular mechanisms and potential therapies. While some such mutations are recurrently found in many tumors, many others exist solely within a few samples, precluding detection by conventional recurrence-based statistical approaches. Integrated analysis of somatic mutations and RNA expression data across 12 tumor types reveals that mutations of cancer genes are usually accompanied by substantial changes in expression. We use topological data analysis to leverage this observation and uncover 38 elusive candidate cancer-associated genes, including inactivating mutations of the metalloproteinase ADAMTS12 in lung adenocarcinoma. We show that ADAMTS12-/- mice have a five-fold increase in the susceptibility to develop lung tumors, confirming the role of ADAMTS12 as a tumor suppressor gene. Our results demonstrate that data integration through topological techniques can increase our ability to identify previously unreported cancer-related alterations.

Hierarchical discovery of large-scale and focal copy number alterations in low-coverage cancer genomes

Background

Detection of DNA copy number alterations (CNAs) is critical to understand genetic diversity, genome evolution and pathological conditions such as cancer. Cancer genomes are plagued with widespread multi-level structural aberrations of chromosomes that pose challenges to discover CNAs of different length scales, and distinct biological origins and functions. Although several computational tools are available to identify CNAs using read depth (RD) signal, they fail to distinguish between large-scale and focal alterations due to inaccurate modeling of the RD signal of cancer genomes. Additionally, RD signal is affected by overdispersion-driven biases at low coverage, which significantly inflate false detection of CNA regions.

Results

We have developed CNAtra framework to hierarchically discover and classify ‘large-scale’ and ‘focal’ copy number gain/loss from a single whole-genome sequencing (WGS) sample. CNAtra first utilizes a multimodal-based distribution to estimate the copy number (CN) reference from the complex RD profile of the cancer genome. We implemented Savitzky-Golay smoothing filter and Modified Varri segmentation to capture the change points of the RD signal. We then developed a CN state-driven merging algorithm to identify the large segments with distinct copy numbers. Next, we identified focal alterations in each large segment using coverage-based thresholding to mitigate the adverse effects of signal variations. Using cancer cell lines and patient datasets, we confirmed CNAtra’s ability to detect and distinguish the segmental aneuploidies and focal alterations. We used realistic simulated data for benchmarking the performance of CNAtra against other single-sample detection tools, where we artificially introduced CNAs in the original cancer profiles. We found that CNAtra is superior in terms of precision, recall and f-measure. CNAtra shows the highest sensitivity of 93 and 97% for detecting large-scale and focal alterations respectively. Visual inspection of CNAs revealed that CNAtra is the most robust detection tool for low-coverage cancer data.

Conclusions

CNAtra is a single-sample CNA detection tool that provides an analytical and visualization framework for CNA profiling without relying on any reference control. It can detect chromosome-level segmental aneuploidies and high-confidence focal alterations, even from low-coverage data. CNAtra is an open-source software implemented in MATLAB^®. It is freely available at https://github.com/AISKhalil/CNAtra.

Copy Number Variation Pattern for Discriminating MACROD2 States of Colorectal Cancer Subtypes

Copy number variation (CNV) is a common structural variation pattern of DNA, and it features a higher mutation rate than single-nucleotide polymorphisms (SNPs) and affects a larger fragment of genomes. CNV is related with the genesis of complex diseases and can thus be used as a strategy to identify novel cancer-predisposing markers or mechanisms. In particular, the frequent deletions of mono-ADP-ribosylhydrolase 2 (MACROD2) locus in human colorectal cancer (CRC) alters DNA repair and the sensitivity to DNA damage and results in chromosomal instability. The relationship between CNV and cancer has not been explained. In this study, on the basis of the genome variation profiling by the SNP array from 651 CRC primary tumors, we computationally analyzed the CNV data to select crucial SNP sites with the most relevance to three different states of MACROD2 (heterozygous deletion, homozygous deletion, and normal state), suggesting that these CNVs may play functional roles in CRC tumorigenesis. Our study can shed new insights into the genesis of cancer based on CNV, providing reference for clinical diagnosis, and treatment prognosis of CRC.

Integrated Genomic, Epigenomic, and Expression Analyses of Ovarian Cancer Cell Lines

To improve our understanding of ovarian cancer, we performed genome-wide analyses of 45 ovarian cancer cell lines. Given the challenges of genomic analyses of tumors without matched normal samples, we developed approaches for detection of somatic sequence and structural changes and integrated these with epigenetic and expression alterations. Alterations not previously implicated in ovarian cancer included amplification or overexpression of ASXL1 and H3F3B, deletion or underexpression of CDC73 and TGF-beta receptor pathway members, and rearrangements of YAP1-MAML2 and IKZF2-ERBB4. Dose-response analyses to targeted therapies revealed unique molecular dependencies, including increased sensitivity of tumors with PIK3CA and PPP2R1A alterations to PI3K inhibitor GNE-493, MYC amplifications to PARP inhibitor BMN673, and SMAD3/4 alterations to MEK inhibitor MEK162. Genome-wide rearrangements provided an improved measure of sensitivity to PARP inhibition. This study provides a comprehensive and broadly accessible resource of molecular information for the development of therapeutic avenues in ovarian cancer.

The overall survival of patients with late-stage ovarian cancer is dismal. To identify therapeutic opportunities, Papp et al. integrate genomic, epigenomic, and expression analyses to provide a resource of molecular abnormalities in ovarian cancer cell lines and use these to identify tumors sensitive to PARP, MEK, and PI3K inhibitors.

Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice

International initiatives such as the Molecular Taxonomy of Breast Cancer International Consortium are collecting multiple data sets at different genome-scales with the aim to identify novel cancer bio-markers and predict patient survival. To analyze such data, several machine learning, bioinformatics, and statistical methods have been applied, among them neural networks such as autoencoders. Although these models provide a good statistical learning framework to analyze multi-omic and/or clinical data, there is a distinct lack of work on how to integrate diverse patient data and identify the optimal design best suited to the available data.In this paper, we investigate several autoencoder architectures that integrate a variety of cancer patient data types (e.g., multi-omics and clinical data). We perform extensive analyses of these approaches and provide a clear methodological and computational framework for designing systems that enable clinicians to investigate cancer traits and translate the results into clinical applications. We demonstrate how these networks can be designed, built, and, in particular, applied to tasks of integrative analyses of heterogeneous breast cancer data. The results show that these approaches yield relevant data representations that, in turn, lead to accurate and stable diagnosis.

Targeted short read sequencing and assembly of re-arrangements and candidate gene loci provide megabase diplotypes

The human genome is composed of two haplotypes, otherwise called diplotypes, which denote phased polymorphisms and structural variations (SVs) that are derived from both parents. Diplotypes place genetic variants in the context of cis-related variants from a diploid genome. As a result, they provide valuable information about hereditary transmission, context of SV, regulation of gene expression and other features which are informative for understanding human genetics. Successful diplotyping with short read whole genome sequencing generally requires either a large population or parent-child trio samples. To overcome these limitations, we developed a targeted sequencing method for generating megabase (Mb)-scale haplotypes with short reads. One selects specific 0.1-0.2 Mb high molecular weight DNA targets with custom-designed Cas9-guide RNA complexes followed by sequencing with barcoded linked reads. To test this approach, we designed three assays, targeting the BRCA1 gene, the entire 4-Mb major histocompatibility complex locus and 18 well-characterized SVs, respectively. Using an integrated alignment- and assembly-based approach, we generated comprehensive variant diplotypes spanning the entirety of the targeted loci and characterized SVs with exact breakpoints. Our results were comparable in quality to long read sequencing.

STRA6 exerts oncogenic role in gastric tumorigenesis by acting as a crucial target of miR-873

Background

Increasing evidence shows that stimulated by retinoic acid 6 (STRA6) participates in regulating multiple cancers. However, the biological roles of STRA6 in gastric cancer (GC) remain unknown. This study aimed to investigate the biological function of STRA6 and reveal the underlying mechanism of its dysregulation in GC.

Methods

The expression level of STRA6 was detected through quantitative real-time PCR and Western blot analysis. The effects of STRA6 on the proliferation of GC cells were studied through CCK-8 proliferation, colony formation and 5-ethynyl-2′-deoxyuridine (EdU) assays. The effects of STRA6 on migration and invasion were detected via wound healing and Transwell assays. Upstream miRNAs, which might regulate STRA6 expression, was predicted through bioinformatics analysis. Their interaction was further confirmed through dual-luciferase reporter assays and rescue experiments.

Results

STRA6 was up-regulated in GC and enhanced the proliferation and metastasis of GC cells in vitro and in vivo. STRA6 knockdown could inhibit the Wnt/β-catenin signalling pathway. STRA6 was confirmed as an miR-873 target, which acted as a tumour suppressor in GC. Rescue assays showed that the repressing effect of miR-873 could be partially reversed by overexpressing STRA6.

Conclusions

STRA6 is down-regulated by miR-873 and plays an oncogenic role by activating Wnt/β-catenin signalling in GC.

Amplification of the EGFR and CCND1 Are Coordinated and Play Important Roles in the Progression of Oral Squamous Cell Carcinomas

Oral squamous cell carcinoma (OSCC) is a common cancer in Taiwan and worldwide. To provide some clues for clinical management of OSCC, 72 advanced-stage OSCCs were analyzed using two microarray platforms (26 cases with Affymetrix 500 K and 46 cases with Affymetrix SNP 6.0). Genomic identification of significant targets in cancer analyses were used to identify significant copy number alterations (CNAs) using a q-value cutoff of 0.25. Among the several significant regions, 12 CNAs were common between these two platforms. Two gain regions contained the well-known oncogenes EGFR (7p11.2) and CCND1 (11q13.3) and several known cancer suppressor genes, such as FHIT (3p14.2-p12.1), FAT1 (4q35.1), CDKN2A (9p21.3), and ATM (11q22.3-q24.3), reside within the 10 deletion regions. Copy number gains of EGFR and CCND1 were further confirmed by fluorescence in situ hybridization and TaqMan CN assay, respectively, in 257 OSCC cases. Our results indicate that EGFR and CCND1 CNAs are significantly associated with clinical stage, tumor differentiation, and lymph node metastasis. Furthermore, EGFR and CCND1 CNAs have an additive effect on OSCC tumor progression. Thus, current genome-wide CNA analysis provides clues for future characterization of important oncogenes and tumor suppressor genes associated with the behaviors of the disease.

A Review on Dietary Intervention in Obesity Associated Colon Cancer

Background: Colorectal cancer (CRC) is one of the major causes of morbidity and mortality. According to National Cancer Registry, the incidence of colorectal cancer in Peninsular Malaysia increases with age. The incidence is highest among Chinese population but lower among Indians and Malays. Many reviews have suggested that obesity may be associated with a higher risk (>50%) of colorectal cancer. Methods: This study collects a comprehensive data from the literature review available from respective journals on dietary intervention and the chemo-protective mechanisms of a few natural resources in obesity -associated colon cancer based on previous and current studies. Results: In obesity-associated colon cancer, the genes of interest and pathways that are mainly involved include NFκB, P13K/Akt, and MAPK pathways, and FTO, leptin, Cyclin D, MMPs, and STAT3 genes. Dietary modification is one of the alternative steps in early prevention of colon cancer. It has been proposed that the components present in certain foods may have the ability to protect against many diseases including the prevention of cancer. Conclusion: There are many factors that lead to obesity-associated colon cancer and the mechanisms behind it is still undergoing intensive research. This review aims to scrutinize research as well as reviews that have been previously reported on obesity associated colorectal cancer and the beneficial effects of including antioxidants-rich foods such as vegetables and fruits in the diet to reduce the risk of obesity associated colorectal cancer.

Instantaneous mutation rate in cancer initiation and progression

BACKGROUND

Cancer is one of the leading causes for the morbidity and mortality worldwide. Although substantial studies have been conducted theoretically and experimentally in recent years, it is still a challenge to explore the mechanisms of cancer initiation and progression. The investigation for these problems is very important for the diagnosis of cancer diseases and development of treatment schemes.

RESULTS

To accurately describe the process of cancer initiation, we propose a new concept of gene initial mutation rate based on our recently designed mathematical model using the non-constant mutation rate. Unlike the widely-used average gene mutation rate that depends on the number of mutations, the gene initial mutation rate can be used to describe the initiation process of a single patient. In addition, we propose the instantaneous tumour doubling time that is a continuous function of time based on the non-constant mutation rate. Our proposed concepts are supported by the clinic data of seven patients with advanced pancreatic cancer. The regression results suggest that, compared with the average mutation rate, the estimated initial mutation rate has a larger value of correlation coefficient with the patient survival time. We also provide the estimated tumour size of these seven patients over time.

CONCLUSIONS

The proposed concepts can be used to describe the cancer initiation and progression for different patients more accurately. Since a quantitative understanding of cancer progression is important for clinical treatment, our proposed model and calculated results may provide insights into the development of treatment schemes and also have other clinic implications.

The clinical implementation of copy number detection in the age of next-generation sequencing

INTRODUCTION

The role of copy number variants (CNVs) in disease is now well established. In parallel NGS technologies, such as long-read technologies, there is continual development and data analysis methods continue to be refined. Clinical exome sequencing data is now a reality for many diagnostic laboratories in both congenital genetics and oncology. This provides the ability to detect and report both SNVs and structural variants, including CNVs, using a single assay for a wide range of patient cohorts. Areas covered: Currently, whole-genome sequencing is mainly restricted to research applications and clinical utility studies. Furthermore, detecting the full-size spectrum of CNVs as well as somatic events remains difficult for both exome and whole-genome sequencing. As a result, the full extent of genomic variants in an individual's genome is still largely unknown. Recently, new sequencing technologies have been introduced which maintain the long-range genomic context, aiding the detection of CNVs and structural variants. Expert commentary: The development of long-read sequencing promises to resolve many CNV and SV detection issues but is yet to become established. The current challenge for clinical CNV detection is how to fully exploit all the data which is generated by high throughput sequencing technologies.

Identification of different mutational profiles in cancers arising in specific colon segments by next generation sequencing

The objective of this study was to investigate the mutational profiles of cancers arising in different colon segments. To this aim, we have analyzed 37 colon cancer samples by use of the Ion AmpliSeq™ Comprehensive Cancer Panel. Overall, we have found 307 mutated genes, most of which already implicated in the development of colon cancer. Among these, 15 genes were mutated in tumors originating in all six colon segments and were defined "common genes" (i.e. APC, PIK3CA, TP53) whereas 13 genes were preferentially mutated in tumors originating only in specific colon segments and were defined "site-associated genes" (i.e. BLNK, PTPRD). In addition, the presence of mutations in 10 of the 307 identified mutated genes (NBN, SMUG1, ERBB2, PTPRT, EPHB1, ALK, PTPRD, AURKB, KDR and GPR124) were found to be of clinical relevance. Among clinically relevant genes, NBN and SMUG1 were identified as independent prognostic factors that predicted poor survival in colon cancer patients. In conclusion, the findings reported here indicate that tumors arising in different colon segments present differences in the type and/or frequency of genetic variants, with two of them being independent prognostic factors that predict poor survival in colon cancer patients.

Prognostic value of microRNAs in colorectal cancer: a meta-analysis

Background

Numerous studies have shown that miRNA levels are closely related to the survival time of patients with colon, rectal, or colorectal cancer (CRC). However, the outcomes of different investigations have been inconsistent. Accordingly, a meta-analysis was conducted to study associations among the three types of cancers.

Materials and methods

Studies published in English that estimated the expression levels of miRNAs with survival curves in CRC were identified until May 20, 2017 by online searches in PubMed, Embase, Web of Science, and the Cochrane Library by two independent authors. Pooled HRs with 95% CIs were used to estimate the correlation between miRNA expression and overall survival.

Results

A total of 63 relevant articles regarding 13 different miRNAs, with 10,254 patients were ultimately included. CRC patients with high expression of blood miR141 (HR 2.52, 95% CI 1.68-3.77), tissue miR21 (HR 1.31, 95% CI 1.12-1.53), miR181a (HR 1.52, 95% CI 1.26-1.83), or miR224 (HR 2.12, 95% CI 1.04-4.34), or low expression of tissue miR126 (HR 1.55, 95% CI 1.24-1.93) had significantly poor overall survival (P<0.05).

Conclusion

In general, blood miR141 and tissue miR21, miR181a, miR224, and miR126 had significant prognostic value. Among these, blood miR141 and tissue miR224 were strong biomarkers of prognosis for CRC.

IRS2 mutations linked to invasion in pleomorphic invasive lobular carcinoma

Pleomorphic invasive lobular carcinoma (PILC) is an aggressive variant of invasive lobular breast cancer that is associated with poor clinical outcomes. Limited molecular data are available to explain the mechanistic basis for PILC behavior. To address this issue, targeted sequencing was performed to identify molecular alterations that define PILC. This sequencing analysis identified genes that distinguish PILC from classic ILC and invasive ductal carcinoma by the incidence of their genomic changes. In particular, insulin receptor substrate 2 (IRS2) is recurrently mutated in PILC, and pathway analysis reveals a role for the insulin receptor (IR)/insulin-like growth factor-1 receptor (IGF1R)/IRS2 signaling pathway in PILC. IRS2 mutations identified in PILC enhance invasion, revealing a role for this signaling adaptor in the aggressive nature of PILC.

Wingless/Wnt Signaling in Intestinal Development, Homeostasis, Regeneration and Tumorigenesis: A Drosophila Perspective

In mammals, the Wnt/β-catenin signal transduction pathway regulates intestinal stem cell maintenance and proliferation, whereas Wnt pathway hyperactivation, resulting primarily from the inactivation of the tumor suppressor Adenomatous polyposis coli (APC), triggers the development of the vast majority of colorectal cancers. The Drosophila adult gut has recently emerged as a powerful model to elucidate the mechanisms by which Wingless/Wnt signaling regulates intestinal development, homeostasis, regeneration, and tumorigenesis. Herein, we review recent insights on the roles of Wnt signaling in Drosophila intestinal physiology and pathology.

The ovarian cancer oncobiome

Humans and other mammals are colonized by microbial agents across the kingdom which can represent a unique microbiome pattern. Dysbiosis of the microbiome has been associated with pathology including cancer. We have identified a microbiome signature unique to ovarian cancers, one of the most lethal malignancies of the female reproductive system, primarily because of its asymptomatic nature during the early stages in development. We screened ovarian cancer samples along with matched, and non-matched control samples using our pan-pathogen array (PathoChip), combined with capture-next generation sequencing. The results show a distinct group of viral, bacterial, fungal and parasitic signatures of high significance in ovarian cases. Further analysis shows specific viral integration sites within the host genome of tumor samples, which may contribute to the carcinogenic process. The ovarian cancer microbiome signature provides insights for the development of targeted therapeutics against ovarian cancers.

RICTOR amplification identifies a subgroup in small cell lung cancer and predicts response to drugs targeting mTOR

Small cell lung cancer (SCLC) is an aggressive cancer that represents ~15% of all lung cancers. Currently there are no targeted therapies to treat SCLC. Our genomic analysis of a metastatic SCLC cohort identified recurrent RICTOR amplification. Here, we examine the translational potential of this observation. RICTOR was the most frequently amplified gene observed (~14% patients), and co-amplified with FGF10 and IL7R on chromosome 5p13. RICTOR copy number variation correlated with RICTOR protein expression in SCLC cells. In parallel, cells with RICTOR copy number (CN) gain showed increased sensitivity to three mTOR inhibitors, AZD8055, AZD2014 and INK128 in cell growth assays, with AZD2014 demonstrating the best inhibition of downstream signaling. SCLC cells with RICTOR CN gain also migrated more rapidly in chemotaxis and scratch wound assays and were again more sensitive to mTOR inhibitors. The overall survival in SCLC patients with RICTOR amplification was significantly decreased (p = 0.021). Taken together, our results suggest that SCLC patients with RICTOR amplification may constitute a clinically important subgroup because of their potential response to mTORC1/2 inhibitors.

Carcinogen 7,12-dimethylbenz[a]anthracene-induced mammary tumorigenesis is accelerated in Smad3 heterozygous mice compared to Smad3 wild type mice

Previous studies based on cell culture and xenograft animal models suggest that Smad3 has tumor suppressor function for breast cancer during early stages of tumorigenesis. In this report, we show that DMBA (7,12-dimethylbenz[a]anthracene), a chemical carcinogen, induces mammary tumor formation at a significantly higher frequency in the Smad3 heterozygous mice than in the Smad3 wild type mice. This is the first genetic evidence showing that Smad3 inhibits mammary tumor formation in a mouse model. Our findings support the notion that Smad3 has important tumor suppressor function for breast cancer.

Integrated Molecular Characterization of the Lethal Pediatric Cancer Pancreatoblastoma

Pancreatoblastoma is a rare pediatric pancreatic malignancy for which the molecular pathogenesis is not understood. In this study, we report the findings of an integrated multiomics study of whole-exome and RNA sequencing as well as genome-wide copy number and methylation analyses of ten pancreatoblastoma cases. The pancreatoblastoma genome was characterized by a high frequency of aberrant activation of the Wnt signaling pathway, either via somatic mutations of CTNNB1 (90%) and copy-neutral loss of heterozygosity (CN-LOH) of APC (10%). In addition, imprinting dysregulation of IGF2 as a consequence of CN-LOH (80%), gain of paternal allele (10%), and gain of methylation (10%) was universally detected. At the transcriptome level, pancreatoblastoma exhibited an expression profile characteristic of early pancreas progenitor-like cells along with upregulation of the R-spondin/LGR5/RNF43 module. Our results offer a comprehensive description of the molecular basis for pancreatoblastoma and highlight rational therapeutic targets for its treatment.Significance: Molecular genetic analysis of a rare untreatable pediatric tumor reveals Wnt/IGF2 aberrations and features of early pancreas progenitor-like cells, suggesting cellular origins and rational strategies for therapeutic targeting. Cancer Res; 78(4); 865-76. ©2017 AACR.