Biology subjects

Roberts, N. J.

Publications and source records attributed to Roberts, N. J..

8 recordsLinked to original sources

bioRxiv2024

Multi-omic profiling of intraductal papillary neoplasms of the pancreas reveals distinct expression patterns and potential markers of progression

In order to advance our understanding of precancers in the pancreas, 69 pancreatic intraductal papillary neoplasms (IPNs), including 64 intraductal papillary mucinous neoplasms (IPMNs) and 5 intraductal oncocytic papillary neoplasms (IOPNs), 32 pancreatic cyst fluid samples, 104 invasive pancreatic ductal adenocarcinomas (PDACs), 43 normal adjacent tissues (NATs), and 76 macro-dissected normal pancreatic ducts (NDs) were analyzed by mass spectrometry. A total of 10,246 proteins and 22,284 glycopeptides were identified in all tissue samples, and 756 proteins with more than 1.5-fold increase in abundance in IPMNs relative to NDs were identified, 45% of which were also identified in cyst fluids. The over-expression of selected proteins was validated by immunolabeling. Proteins and glycoproteins overexpressed in IPMNs included those involved in glycan biosynthesis and the immune system. In addition, multiomics clustering identified two subtypes of IPMNs. This study provides a foundation for understanding tumor progression and targets for earlier detection and therapies. SignificanceThis multilevel characterization of intraductal papillary neoplasms of the pancreas provides a foundation for understanding the changes in protein and glycoprotein expression during the progression from normal duct to intraductal papillary neoplasm, and to invasive pancreatic carcinoma, providing a foundation for informed approaches to earlier detection and treatment.

cancer biology↗

bioRxiv2024

Islands of genomic stability in the face of genetically unstable metastatic cancer

AbstractO_ST_ABSIntroductionC_ST_ABSMetastatic cancer affects millions of people worldwide annually and is the leading cause of cancer-related deaths. Most patients with metastatic disease are not eligible for surgical resection, and current therapeutic regimens have varying success rates, some with 5-year survival rates below 5%. Here we test the hypothesis that metastatic cancer can be genetically targeted by exploiting single base substitution mutations unique to individual cells that occur as part of normal aging prior to transformation. These mutations are targetable because [~]10% of them form novel tumor-specific "NGG" protospacer adjacent motif (PAM) sites targetable by CRISPR-Cas9. MethodsWhole genome sequencing was performed on five rapid autopsy cases of patient-matched primary tumor, normal and metastatic tissue from pancreatic ductal adenocarcinoma decedents. CRISPR-Cas9 PAM targets were determined by bioinformatic tumor-normal subtraction for each patient and verified in metastatic samples by high-depth capture-based sequencing. ResultsWe found that 90% of PAM targets were maintained between primary carcinomas and metastases overall. We identified rules that predict PAM loss or retention, where PAMs located in heterozygous regions in the primary tumor can be lost in metastases (private LOH), but PAMs occurring in regions of loss of heterozygosity (LOH) in the primary tumor were universally conserved in metastases. ConclusionsRegions of truncal LOH are strongly retained in the presence of genetic instability, and therefore represent genetic vulnerabilities in pancreatic adenocarcinomas. A CRISPR-based gene therapy approach targeting these regions may be a novel way to genetically target metastatic cancer.

cancer biology↗

bioRxiv2023

Functional characterization of all CDKN2A missense variants and comparison to in silico models of pathogenicity

Interpretation of variants identified during genetic testing is a significant clinical challenge. In this study, we developed a high-throughput CDKN2A functional assay and characterized all possible CDKN2A missense variants. We found that 17.7% of all missense variants were functionally deleterious. We also used our functional classifications to assess the performance of in silico models that predict the effect of variants, including recently reported models based on machine learning. Notably, we found that all in silico models performed similarly when compared to our functional classifications with accuracies of 39.5-85.4%. Furthermore, while we found that functionally deleterious variants were enriched within ankyrin repeats, we did not identify any residues where all missense variants were functionally deleterious. Our functional classifications are a resource to aid the interpretation of CDKN2A variants and have important implications for the application of variant interpretation guidelines, particularly the use of in silico models for clinical variant interpretation.

genetics↗

bioRxiv2023

Somatic protospacer adjacent motifs are numerous and selectively targetable in cancers

Somatic mutations are desirable targets for selective elimination of cancer, yet most are found within the noncoding regions. We propose a novel, cancer-specific killing approach using CRISPR-Cas9 which exploits the requirement of a protospacer adjacent motif (PAM) for Cas9 activity. Through whole genome sequencing (WGS) of paired tumor minus normal (T-N) samples from three pancreatic cancer patients (Panc480, Panc504, and Panc1002), we identified an average of 417 somatic PAMs per tumor produced from single base substitutions. We analyzed 591 paired T-N samples from The International Cancer Genome Consortium and discovered medians of [~]455 somatic PAMs per tumor in pancreatic, [~]2800 in lung, and [~]3200 in esophageal cancer cohorts. Finally, we demonstrated >80% selective cell death of two targeted pancreatic cancer cell lines in co-cultures using 4-9 sgRNAs, targeting noncoding regions, designed from the somatic PAM discovery approach. We also showed no off-target activity from these tumor-specific sgRNAs through WGS. Statement of significanceThis study demonstrates the potential of CRISPR-Cas9 as a novel and selective anti-cancer strategy. It requires just a few targets to induce double strand breaks for significant cytotoxicity. Our findings markedly expand the repertoire of targetable mutations in cancers and support genetically targeting other adult solid tumor types.

cancer biology↗

bioRxiv2023

Mechanism of delayed cell death following simultaneous CRISPR-Cas9 targeting in pancreatic cancers

While radiation is an effective oncologic therapy, killing cancer by inducing DNA double-strand breaks (DSBs), it lacks specificity for neoplastic cells. We have previously adapted the CRISPR-Cas9 gene-editing technology as a cancer-specific treatment modality targeting somatic mutations in pancreatic cancer (PC). However, its tumoricidal potential remains unclear, especially in comparison to therapeutic doses of radiation. Here, we demonstrate that CRISPR-Cas9-induced DSBs are more cytotoxic in PCs than a comparable number of radiation-induced DSBs. We observed >90% tumor growth inhibition by targeting 9 sites with cancer-specific single-guide RNAs (sgRNAs). Through both bioinformatics and cytogenetics analyses, we found that CRISPR-Cas9-induced DSBs triggered ongoing chromosomal rearrangements, with 87% of structural variants not directly produced from the initial CRISPR-Cas9-induced DSBs, and chromosomal instability (CIN) peaking before cell death. By comparing the cytotoxicity of CRISPR-Cas9- to radiation-induced DSBs, we demonstrate that the number of DSBs required to achieve equitoxic effects was [~]3 times higher for radiation than CRISPR-Cas9. Finally, we show that PC cells that had survived CRISPR-Cas9 targeting retained susceptibility to subsequent CRISPR-Cas9-induced DSBs at different genomic sites with >87% growth inhibition. Together, our data support the therapeutic potential of CRISPR-Cas9 as an anti-cancer strategy.

cancer biology↗

bioRxiv2023

Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions

Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS, but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.

cancer biology↗

bioRxiv2022

Evolutionary history mediates population response to rapid environmental change through within-generational and transgenerational plasticity

Rapid environmental change is affecting many organisms; some are coping well but many species are in decline. A key mechanism for facilitating success following environmental change is phenotypic plasticity. Organisms use cues to respond phenotypically to environmental conditions; many incorporate recent information (within-generation plasticity) and information from previous generations (transgenerational plasticity). We extend an existing evolutionary model where organisms utilize within-generational plasticity, transgenerational plasticity, rapid evolution, and bet-hedging. We show how, when rapid evolution of plasticity is not possible, the effect of environmental change (altering the environment mean, variance, or autocorrelation, or cue reliability) on population growth rate depends on selection for within-generation plasticity and transgenerational plasticity under historical environmental conditions. We then evaluate the predictions that populations adapted to highly variable environments, or with greater within-generational plasticity, are more likely to successfully respond to environmental change. We identify when these predictions fail, and show environmental change is most detrimental when previously reliable cues become unreliable. When multiple cues become unreliable, environmental change can cause deleterious effects regardless of the populations evolutionary history. Overall, this work provides a general framework for understanding the role of plasticity in population responses to rapid environmental change.

evolutionary biology↗

bioRxiv2021

Transcriptomic Insights into the Responses in Leaves Storing Lipid Organelles under Different Irradiances

To increase the nutritional value of forage, transgenic ryegrass known as High Metabolizable Energy (HME) were previously generated that co-express cysteine-oleosin and diacylglycerol O-acyltransferase. HME not only accumulate lipids in the leaf but also has elevated CO2 assimilation and increased biomass. Shading is one of the most influencing factors for ryegrass growth environments particularly in swards. The aim of this study, therefore, was to determine the influence of irradiance levels on photosynthesis and gene expression in the HME leaves when compared with their corresponding non-transformant (NT). Under low light (150-250 {micro}mol m-2 s-1) and standard light (600-1000 {micro}mol m-2 s-1), the HME accumulated more lipid than NT. The previously reported elevated photosynthesis and increased biomass was observed when the HME were grown under standard light but not under low light. Under both light conditions, compared to NT, the HME had upregulated a number of transcripts involved in lipid metabolism, light capturing, photosynthesis, and sugar signalling network while downregulated genes participated in sugar and fructan biosynthesis. We further discuss how the HME differentially manipulated several genes other metabolic pathways including maintenance of redox homeostasis. Combined, the data suggests that the increased photosynthesis capacity in the HME likely corresponds to an increase of micro-lipid sink strength; these are influenced by available light energy and may be related to diffusional and biochemical activities of stomata. Overall, this work provides a clearly understanding of the changes in molecular and biochemical mechanisms underlying the carbon storing as leaf lipid sink of the HME ryegrass. One sentence summaryShading led to increase leaf lipid accumulation but limit the greater photosynthesis trait of high lipid ryegrass which may be related to limitation of biochemical activities of stomata.

molecular biology↗