Comprehensive evaluation of coding region point mutations in microsatellite-unstable colorectal cancer

Mapping protein-protein interactions by mass spectrometry

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

Genomic profiling of small bowel adenocarcinoma: a pooled analysis from 3 databases

BACKGROUND

Small bowel adenocarcinoma is a rare disease. The genomic profiling tumours according to clinical characteristics and its impact on the prognosis remains unclear.

METHODS

A pooled analysis of clinical data, genomic profiling and MisMatch Repair (MMR) status from three databases was performed.

RESULTS

A total of 188 tumour samples were analysed. A predisposing disease was reported in 22.3%, mainly Lynch syndrome and Crohn's disease. The tumours were localized in 80.2% and metastatic in 18.8%. The most frequent mutations were KRAS (42.0%) among them 7/79 are G12C, TP53 (40.4%), APC (19.1%), PIK3CA (18.6%), SMAD4 (12.8%) and ERBB2 (9.6%). Mutation distribution differed according to predisposing disease for TP53, ERBB2, IDH1, FGFR3, FGFR1 and KDR. KRAS and SMAD4 mutations were more frequent in metastatic tumour, whereas ERBB2 mutations were absent in metastatic tumour. For localized tumour, APC mutation was independently associated with a poor overall survival (OS) (p = 0.0254). 31.8% of localized tumours and 11.3% of metastatic tumours were dMMR (29.8% of the entire cohort). A dMMR status was associated with a better OS (HR = 0.61 [0.39-0.96], p = 0.0316).

CONCLUSIONS

There is a different genomic profile according to the stage and predisposing disease. dMMR and APC mutation in localized tumour predict a better prognosis.

Illumination of understudied ciliary kinases

Cilia are cellular signaling hubs. Given that human kinases are central regulators of signaling, it is not surprising that kinases are key players in cilia biology. In fact, many kinases modulate ciliogenesis, which is the generation of cilia, and distinct ciliary pathways. Several of these kinases are understudied with few publications dedicated to the interrogation of their function. Recent efforts to develop chemical probes for members of the cyclin-dependent kinase like (CDKL), never in mitosis gene A (NIMA) related kinase (NEK), and tau tubulin kinase (TTBK) families either have delivered or are working toward delivery of high-quality chemical tools to characterize the roles that specific kinases play in ciliary processes. A better understanding of ciliary kinases may shed light on whether modulation of these targets will slow or halt disease onset or progression. For example, both understudied human kinases and some that are more well-studied play important ciliary roles in neurons and have been implicated in neurodevelopmental, neurodegenerative, and other neurological diseases. Similarly, subsets of human ciliary kinases are associated with cancer and oncological pathways. Finally, a group of genetic disorders characterized by defects in cilia called ciliopathies have associated gene mutations that impact kinase activity and function. This review highlights both progress related to the understanding of ciliary kinases as well as in chemical inhibitor development for a subset of these kinases. We emphasize known roles of ciliary kinases in diseases of the brain and malignancies and focus on a subset of poorly characterized kinases that regulate ciliary biology.

The putative oncogenic role of WDTC1 in colorectal cancer

Microsatellite instability (MSI) is detected in approximately 15% of colorectal cancers (CRCs). WD40 and tetratricopeptide repeats 1 (WDTC1) is frequently mutated in MSI CRC, indicating that it may contribute to CRC development. However, the functional evidence of the role of WDTC1 in CRC development remains unknown. Herein, we conducted in vitro assays to examine the function of WDTC1 using knockdown experiments in three CRC cell lines, SW480, CACO2, and LoVo. We provided strong evidence that silencing WDTC1 significantly suppressed cell proliferation, migration, and invasion consistently in all three CRC cell lines. To evaluate the potential role of WDTC1 in regulating CRC-related genes, we conducted RNA sequencing after 24 and 48 h in SW480 cells after treating WDTC1-siRNA and its vehicle control cells. Differential gene expression analysis identified 44 (42 downregulated and 2 upregulated) and 16 (all downregulated) genes, at time points of 24 and 48 h, respectively, whereas 15 downregulated genes were commonly detected at both time points. The ingenuity pathways analysis suggested that the most significant enrichments associated with cancer function and upstream regulator ATM/ATR were observed for these commonly observed genes. We further verified differential gene expression of eight cancer-related genes, ARHGEF12, GSTP1, FNDC3A, TMTC3, RTN4, RRM2, UHMK1, and PTPRF, using RT-PCR in all three cell lines. Our findings provided additional insight into the oncogenic role of WDTC1 in CRC development.

fdrci: FDR confidence interval selection and adjustment for large-scale hypothesis testing

Motivation

Approaches that control error by applying a priori fixed discovery thresholds such as 0.05 limit the ability of investigators to identify and publish weak effects even when evidence suggests that such effects exist. However, current false discovery rate (FDR) estimation methods lack a principled approach for post hoc identification of discovery thresholds other than 0.05.

Results

We describe a flexible approach that hinges on the precision of a permutation-based FDR estimator. A series of discovery thresholds are proposed, and an FDR confidence interval selection and adjustment technique is used to identify intervals that do not cover one, implying that some discoveries are expected to be true. We report an application to a transcriptome-wide association study of the MAVERICC clinical trial involving patients with metastatic colorectal cancer. Several genes are identified whose predicted expression is associated with progression-free or overall survival.

Availability and implementation

Software is provided via the CRAN repository (https://cran.r-project.org/web/packages/fdrci/index.html).

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Evaluation of a Targeted Next-Generation Sequencing Panel for the Non-Invasive Detection of Variants in Circulating DNA of Colorectal Cancer

Molecular profiling of circulating cell-free DNA (cfDNA) has shown utility for the management of colorectal cancer (CRC). TruSight Tumor 170 (TST170) is a next-generation sequencing (NGS) panel that covers 170 cancer-related genes, including KRAS, which is a key driver gene in CRC. We evaluated the capacity of TST170 to detect gene variants in cfDNA from a retrospective cohort of 20 metastatic CRC patients with known KRAS variants in tumor tissue and in cfDNA previously analyzed by pyrosequencing and BEAMing, respectively. The cfDNA of most of the patients (95%) was successfully sequenced. We frequently detected variants with clinical significance in KRAS (79%, 15/19) and PIK3CA (26%, 5/19) genes. Variants with potential clinical significance were also identified in another 27 cancer genes, such as APC. The type of KRAS variant detected in cfDNA by TST170 showed high concordance with those detected in tumor tissue (77%), and very high concordance with cfDNA analyzed by BEAMing (94%). The variant allele fractions for KRAS obtained in cfDNA by TST170 and BEAMing correlated strongly. This proof-of-principle study indicates that targeted NGS analysis of cfDNA with TST170 could be useful for non-invasive detection of gene variants in metastatic CRC patients, providing an assay that could be easily implemented for detecting somatic alterations in the clinic.

Expression of Immuno-Oncologic Biomarkers Is Enriched in Colorectal Cancers and Other Solid Tumors Harboring the A59T Variant of KRAS

The molecular heterogeneity of KRAS is well established, with a pool of variants comprising >75% of all known mutations; this pool includes mutations in classic codons 12, 13, and 61, as well as 146 and 117. In addition, there are rare variants that are more frequently encountered clinically due to the advances in next-generation sequencing and more widespread implementation of All-RAS sequencing over the past five years. We have previously identified a missense variant of KRAS, A59T, in a patient with CRC that was associated with a response to an epidermal growth factor inhibitor when added to chemotherapy, supporting the hypothesis that distinct biochemical impacts of different KRAS mutations may produce varied responses to targeted therapy. In this study, we explored a large genomic database comprising 17,909 cases of CRC to determine the prevalence of the A59T mutation and characterized the concurrent genomic alterations associated with this variant in more detail, particularly in relation to the expanding set of potential predictive immuno-oncologic biomarkers. We identified 14 cases of A59 mutations in this dataset (0.08% prevalence). We evaluated the prevalence of high tumor mutation burden (TMB), positive PD-L1 expression, and microsatellite instability-high/mismatch repair-deficiency (MSI-H/dMMR) using both next generation sequencing (NGS) and immunohistochemistry (IHC). The genomic features of pertinent signaling pathways were also described, including RAS pathway, chromatin remodeling, DDR, hedgehog signaling, PI3K, receptor tyrosine kinases, signal transduction, TGF-beta, TP53, and WNT. We uncovered a high level of association of predictive markers of responsiveness to checkpoint inhibition and potentially other forms of immunotherapy, with nearly half of all cases harboring microsatellite instability as assessed using NGS. A59T was also detected in 11 additional cancer types, most prominently in cases of gynecologic or other gastrointestinal sites of origin. This study provides supportive evidence that A59T, and possibly other similarly rare KRAS variants, co-occur with predictive biomarkers of response to immunotherapy.

Joint analysis of expression levels and histological images identifies genes associated with tissue morphology

Histopathological images are used to characterize complex phenotypes such as tumor stage. Our goal is to associate features of stained tissue images with high-dimensional genomic markers. We use convolutional autoencoders and sparse canonical correlation analysis (CCA) on paired histological images and bulk gene expression to identify subsets of genes whose expression levels in a tissue sample correlate with subsets of morphological features from the corresponding sample image. We apply our approach, ImageCCA, to two TCGA data sets, and find gene sets associated with the structure of the extracellular matrix and cell wall infrastructure, implicating uncharacterized genes in extracellular processes. We find sets of genes associated with specific cell types, including neuronal cells and cells of the immune system. We apply ImageCCA to the GTEx v6 data, and find image features that capture population variation in thyroid and in colon tissues associated with genetic variants (image morphology QTLs, or imQTLs), suggesting that genetic variation regulates population variation in tissue morphological traits.

No evidence of EMAST in whole genome sequencing data from 248 colorectal cancers

Microsatellite instability (MSI) is caused by defective DNA mismatch repair (MMR), and manifests as accumulation of small insertions and deletions (indels) in short tandem repeats of the genome. Another form of repeat instability, elevated microsatellite alterations at selected tetranucleotide repeats (EMAST), has been suggested to occur in 50% to 60% of colorectal cancer (CRC), of which approximately one quarter are accounted for by MSI. Unlike for MSI, the criteria for defining EMAST is not consensual. EMAST CRCs have been suggested to form a distinct subset of CRCs that has been linked to a higher tumor stage, chronic inflammation, and poor prognosis. EMAST CRCs not exhibiting MSI have been proposed to show instability of di- and trinucleotide repeats in addition to tetranucleotide repeats, but lack instability of mononucleotide repeats. However, previous studies on EMAST have been based on targeted analysis of small sets of marker repeats, often in relatively few samples. To gain insight into tetranucleotide instability on a genome-wide level, we utilized whole genome sequencing data from 227 microsatellite stable (MSS) CRCs, 18 MSI CRCs, 3 POLE-mutated CRCs, and their corresponding normal samples. As expected, we observed tetranucleotide instability in all MSI CRCs, accompanied by instability of mono-, di-, and trinucleotide repeats. Among MSS CRCs, some tumors displayed more microsatellite mutations than others as a continuum, and no distinct subset of tumors with the previously proposed molecular characters of EMAST could be observed. Our results suggest that tetranucleotide repeat mutations in non-MSI CRCs represent stochastic mutation events rather than define a distinct CRC subclass.

Panel gene profiling of small bowel adenocarcinoma: Results from the NADEGE prospective cohort

Small bowel adenocarcinoma (SBA) is a rare tumour. Large genomic analyses with prognostic assessments are lacking. The NADEGE cohort has enrolled 347 patients with all stage SBA from 2009 to 2012. Next-generation sequencing investigates the presence of 740 hotspot somatic mutations in a panel of 46 genes involved in carcinogenesis. The mismatch repair (MMR) status was assessed by immunochemistry. We have collected 196 tumour samples and 125 had conclusive results for mutation analysis. The number of mutations was 0 in 9.6% of tumours, only 1 in 32.0%, 2 in 26.4% and ≥3 in 32.0%. Overall, at least one genomic alteration was observed in 90.4% of tumour. The most frequent genomic alteration was in KRAS (44.0%), TP53 (38.4%), PIK3CA (20.0%), APC (18.4%), SMAD4 (14.4%) and ERBB2 (7.2%) genes. KRAS mutations were more frequent in synchronous metastatic tumours than in localised tumours (72.7% vs 38.2%, P = .003). There was no significant difference in the mutation rates according to primary location for the most frequently altered gene. ATM, FGFR3 and FGFR1 gene alterations were associated with Lynch syndrome and IDH1 mutations with Crohn disease. dMMR tumours were associated with younger age, localised tumours, less KRAS but more SMARCB1 mutations. No genomic alteration was associated with overall survival. There is a trend for better survival in patient with dMMR tumours. In conclusion, there is a different genomic alteration profile in SBA according to predisposing diseases. No association between genomic alterations and prognoses was observed except for a trend of better prognoses associated with dMMR.

Combined proximity labeling and affinity purification-mass spectrometry workflow for mapping and visualizing protein interaction networks

Affinity purification coupled with mass spectrometry (AP-MS) and proximity-dependent biotinylation identification (BioID) methods have made substantial contributions to interaction proteomics studies. Whereas AP-MS results in the identification of proteins that are in a stable complex, BioID labels and identifies proteins that are in close proximity to the bait, resulting in overlapping yet distinct protein identifications. Integration of AP-MS and BioID data has been shown to comprehensively characterize a protein's molecular context, but interactome analysis using both methods in parallel is still labor and resource intense with respect to cell line generation and protein purification. Therefore, we developed the Multiple Approaches Combined (MAC)-tag workflow, which allows for both AP-MS and BioID analysis with a single construct and with almost identical protein purification and mass spectrometry (MS) identification procedures. We have applied the MAC-tag workflow to a selection of subcellular markers to provide a global view of the cellular protein interactome landscape. This localization database is accessible via our online platform ( http://proteomics.fi ) to predict the cellular localization of a protein of interest (POI) depending on its identified interactors. In this protocol, we present the detailed three-stage procedure for the MAC-tag workflow: (1) cell line generation for the MAC-tagged POI; (2) parallel AP-MS and BioID protein purification followed by MS analysis; and (3) protein interaction data analysis, data filtration and visualization with our localization visualization platform. The entire procedure can be completed within 25 d.