Tumor diversity and evolution revealed through RADseq

Restriction site associated DNA sequencing for tumour mutation burden estimation and mutation signature analysis

BACKGROUND

Genome-wide measures of genetic disruption such as tumour mutation burden (TMB) and mutation signatures are emerging as useful biomarkers to stratify patients for treatment. Clinicians commonly use cancer gene panels for tumour mutation burden estimation, and whole genome sequencing is the gold standard for mutation signature analysis. However, the accuracy and cost associated with these assays limits their utility at scale.

METHODS

WGS data from 560 breast cancer patients was used for in silico library simulations to evaluate the accuracy of an FDA approved cancer gene panel as well as restriction enzyme associated DNA sequencing (RADseq) libraries for TMB estimation and mutation signature analysis. We also transfected a mouse mammary cell line with APOBEC enzymes and sequenced resulting clones to evaluate the efficacy of RADseq in an experimental setting.

RESULTS

RADseq had improved accuracy of TMB estimation and derivation of mutation profiles when compared to the FDA approved cancer panel. Using simulated immune checkpoint blockade (ICB) trials, we show that inaccurate TMB estimation leads to a reduction in power for deriving an optimal TMB cutoff to stratify patients for immune checkpoint blockade treatment. Additionally, prioritisation of APOBEC hypermutated tumours in these trials optimises TMB cutoff determination for breast cancer. The utility of RADseq in an experimental setting was also demonstrated, based on characterisation of an APOBEC mutation signature in an APOBEC3A transfected mouse cell line.

CONCLUSION

In conclusion, our work demonstrates that RADseq has the potential to be used as a cost-effective, accurate solution for TMB estimation and mutation signature analysis by both clinicians and basic researchers.

Down-regulation of metabolic pathways could offset the poor prognosis conferred by co-existent diabetes mellitus in pancreatic (head) adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) patients with diabetes mellitus (DM) have poor overall survival. Underlying mechanisms have not been fully clarified. This presents an opportunity for precision-oncology for which we systematically analysed publicly-available PDAC transcriptome data.

METHODS

PDAC TCGA RNASeq data were used. Analyses were restricted to only 'high purity' and 'head' as anatomical site. Patients were characterised by: (1) Gene expression classification, and (2) Weighted gene correlation network analysis (WGCNA) to identify co-expression patterns of genes. Newly identified gene signature subclasses of pancreatic head PDAC were associated with clinical and functional characteristics of patients.

RESULTS

Consensus clustering identified two patient subclasses within PDAC involving pancreatic head. WGCNA identified 11 distinct networks of gene expression patterns across two sub-classes. Class 1 patients demonstrated a significant upregulation of Module 5 and Module 6 gene expression compared to Class 2. Class 1 predominantly expressed the acinar, ductal and islet cell gene signatures. There were significantly less patients with DM in Class 1 subclass compared to Class 2 (p < 0.037). Patients with DM had significant downregulation of pathways involved in cellular metabolism, hormone secretion and paucity of islet cell markers with no reduced survival compared with non-diabetics.

CONCLUSIONS

A significant proportion of patients with PDAC of pancreatic head and DM exhibit downregulation of pathways involved in cellular metabolism, hormone secretion and signalling accompanied by a paucity of islet expression. Investigating the relationship between DM and gene expression profiles in patients with PDAC presents opportunities to improve overall survival in diabetics with PDAC.

Significance and limitations of the use of next-generation sequencing technologies for detecting mutational signatures

Next generation sequencing technologies (NGS) have been critical in characterizing the genomic landscape and untangling the genetic heterogeneity of human cancer. Since its advent, NGS has played a pivotal role in identifying the patterns of somatic mutations imprinted on cancer genomes and in deciphering the signatures of the mutational processes that have generated these patterns. Mutational signatures serve as phenotypic molecular footprints of exposures to environmental factors as well as deficiency and infidelity of DNA replication and repair pathways. Since the first roadmap of mutational signatures in human cancer was generated from whole-genome and whole-exome sequencing data, there has been a growing interest to extract mutational signatures from other NGS technologies such as targeted panel sequencing, RNA sequencing, single-cell sequencing, duplex sequencing, reduced representation sequencing, and long-read sequencing. Many of these technologies have their inherent sequencing biases and produce technical artifacts that can confound the extraction of reliable and interpretable mutational signatures. In this review, we highlight the relevance, limitations, and prospects of using different NGS technologies for examining mutational patterns and for deciphering mutational signatures.

The mutREAD method detects mutational signatures from low quantities of cancer DNA

Mutational processes acting on cancer genomes can be traced by investigating mutational signatures. Because high sequencing costs limit current studies to small numbers of good-quality samples, we propose a robust, cost- and time-effective method, called mutREAD, to detect mutational signatures from small quantities of DNA, including degraded samples. We show that mutREAD recapitulates mutational signatures identified by whole genome sequencing, and will ultimately allow the study of mutational signatures in larger cohorts and, by compatibility with formalin-fixed paraffin-embedded samples, in clinical settings.

Effects of the MDM-2 inhibitor Nutlin-3a on PDAC cells containing and lacking WT-TP53 on sensitivity to chemotherapy, signal transduction inhibitors and nutraceuticals

Mutations at the TP53 gene are readily detected (approximately 50-75%) in pancreatic ductal adenocarcinoma (PDAC) patients. TP53 was previously thought to be a difficult target as it is often mutated, deleted or inactivated on both chromosomes in certain cancers. In the following study, the effects of restoration of wild-type (WT) TP53 activity on the sensitivities of MIA-PaCa-2 pancreatic cancer cells to the MDM2 inhibitor nutlin-3a in combination with chemotherapy, targeted therapy, as well as, nutraceuticals were examined. Upon introduction of the WT-TP53 gene into MIA-PaCa-2 cells, which contain a TP53 gain of function (GOF) mutation, the sensitivity to the MDM2 inhibitor increased. However, effects of nutlin-3a were also observed in MIA-PaCa-2 cells lacking WT-TP53, as upon co-treatment with nutlin-3a, the sensitivity to certain inhibitors, chemotherapeutic drugs and nutraceuticals increased. Interestingly, co-treatment with nutlin-3a and certain chemotherapeutic drug such as irinotecan and oxaliplatin resulted in antagonistic effects in cells both lacking and containing WT-TP53 activity. These studies indicate the sensitizing abilities that WT-TP53 activity can have in PDAC cells which normally lack WT-TP53, as well as, the effects that the MDM2 inhibitor nutlin-3a can have in both cells containing and lacking WT-TP53 to various therapeutic agents.

Introduction of WT-TP53 into pancreatic cancer cells alters sensitivity to chemotherapeutic drugs, targeted therapeutics and nutraceuticals

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive, highly metastatic malignancy and accounts for 85% of pancreatic cancers. PDAC patients have poor prognosis with a five-year survival of only 5-10%. Mutations at the TP53 gene are readily detected in pancreatic tumors isolated from PDAC patients. We have investigated the effects of restoration of wild-type (WT) TP53 activity on the sensitivity of pancreatic cancer cells to: chemotherapy, targeted therapy, as well as, nutraceuticals. Upon introduction of the WT-TP53 gene into the MIA-PaCa-2 pancreatic cancer cell line, the sensitivity to drugs used to treat pancreatic cancer cells such as: gemcitabine, fluorouracil (5FU), cisplatin, irinotecan, oxaliplatin, and paclitaxel increased significantly. Likewise, the sensitivity to drugs used to treat other cancers such as: doxorubicin, mitoxantrone, and 4 hydroxy tamoxifen (4HT) also increased upon introduction of WT-TP53 into MIA-PaCa-2 cells. Furthermore, the sensitivity to certain inhibitors which target: PI3K/mTORC1, PDK1, SRC, GSK-3, and biochemical processes such as proteasomal degradation and the nutraceutical berberine as increased upon introduction of WT-TP53. Furthermore, in some cases, cells with WT-TP53 were more sensitive to the combination of drugs and suboptimal doses of the MDM2 inhibitor nutlin-3a. However, TP53-independent effects of nutlin-3a were observed upon treatment with either a proteasomal or a PI3K/mTOR inhibitor. These studies indicate the sensitizing effects that WT-TP53 can have in PDAC cells which normally lack WT-TP53 to various therapeutic agents and suggest approaches to improve PDAC therapy.