Pancreatic cancer actionable genes in precision medicine and personalized surgery

Comprehensive molecular profiling of pancreatic ductal adenocarcinoma in FNA, biopsy, and resection specimens

BACKGROUND

Molecular testing to identify molecular alterations in pancreatic ductal adenocarcinoma (PDAC) has been increasingly requested because of potential therapeutic implications. In this study, we compared the performance of PDAC fine-needle aspiration (FNA), fine-needle biopsy (FNB), and resection specimens for comprehensive molecular analysis.

METHODS

A next-generation sequencing-based Oncomine Comprehensive Assay (OCA) was used to analyze molecular alterations in FNA, FNB, or resection specimens. We examined adequacy and success rates for completion of molecular testing and catalogued molecular alterations in these specimen types.

RESULTS

The cohort included 23 FNA, 20 FNB, and 27 resection cases. Gene mutation or amplification analysis was successful in 18 (78%) FNA and 16 (80%) FNB specimens, whereas gene fusion assessment succeeded in 12 (52%) FNA and 12 (60%) FNB samples. All 27 (100%) resection specimens were adequate for complete OCA. There were significant differences in success rates for mutation and amplification analysis between resection and FNA or FNB specimens (P < .01) but not between FNA and FNB samples (P > .05). Manual microdissection was less likely to be performed for FNA specimens than FNB or resection specimens (P < .01). KRAS mutation was the most common mutation identified (90%), followed by mutations in TP53 (64%), CDKN2A (25%), and SMAD4 (15%) genes.

CONCLUSIONS

Our study demonstrated similar success rates for comprehensive molecular analysis using FNA and FNB specimens of PDAC, suggesting that FNA material could serve as an alternative source for comprehensive molecular testing. The molecular alterations identified in these specimens may have potential diagnostic and therapeutic implications.

The Crossroads of Precision Medicine and Therapeutic Decision-Making: Use of an Analytical Computational Platform to Predict Response to Cancer Treatments

Metastatic cancer is a medical challenge that has been historically resistant to treatments. One area of leverage in cancer care is the development of molecularly-driven combination therapies, offering the possibility to overcome resistance. The selection of optimized treatments based on the complex molecular features of a patient’s tumor may be rendered easier by using a computer-assisted program. We used the PreciGENE^® platform that uses multi-pathway molecular analysis to identify personalized therapeutic options. These options are ranked using a predictive score reflecting the degree to which a therapy or combination of therapies matches the patient’s biomarker profile. We searched PubMed from February 2010 to June 2017 for all patients described as exceptional responders who also had molecular data available. Altogether, 70 patients with cancer who had received 202 different treatment lines and who had responded (stable disease ≥12 months/partial or complete remission) to ≥1 regimen were curated. We demonstrate that an algorithm reflecting the degree to which patients were matched to the drugs administered correctly ranked the response to the regimens with a sensitivity of 84% and a specificity of 77%. The difference in matching score between successful and unsuccessful treatment lines was significant (median, 65% versus 0%, p-value <0.0001).

Liquid biopsy in pancreatic cancer: the beginning of a new era

With dismal survival rate pancreatic cancer remains one of the most aggressive and devastating malignancy. Predominantly, due to the absence of a dependable methodology for early identification and limited therapeutic options for advanced disease. However, it takes over 17 years to develop pancreatic cancer from initiation of mutation to metastatic cancer; therefore, if diagnosed early; it may increase overall survival dramatically, thus, providing a window of opportunity for early detection. Recently, genomic expression analysis defined 4 subtypes of pancreatic cancer based on mutated genes. Hence, we need simple and standard, minimally invasive test that can monitor those altered genes or their associated pathways in time for the success of precision medicine, and liquid biopsy seems to be one answer to all these questions. Again, liquid biopsy has an ability to pair with genomic tests. Additionally, liquid biopsy based development of circulating tumor cells derived xenografts, 3D organoids system, real-time monitoring of genetic mutations by circulating tumor DNA and exosome as the targeted drug delivery vehicle holds lots of potential for the treatment and cure of pancreatic cancer. At present, diagnosis of pancreatic cancer is frantically done on the premise of CA19-9 and radiological features only, which doesn't give a picture of genetic mutations and epigenetic alteration involved. In this manner, the current diagnostic paradigm for pancreatic cancer diagnosis experiences low diagnostic accuracy. This review article discusses the current state of liquid biopsy in pancreatic cancer as diagnostic and therapeutic tools and future perspectives of research in the light of circulating tumor cells, circulating tumor DNA and exosomes.

Translational genomics in pancreatic ductal adenocarcinoma: A review with re-analysis of TCGA dataset

Malignancy of the pancreas is a leading cause of cancer-related mortality, with the highest case-fatality of all cancers. Nevertheless, the lack of sensitive biomarkers and presence of biological heterogeneity precludes its early detection and effective treatment. The recent introduction of next-generation sequencing allows characterization of multiple driver mutations at genome- and exome-wide levels. Sequencing of DNA and RNA from circulating tumour cells has also opened an exciting era of non-invasive procedures for tumour detection and prognostication. This massively-parallel sequencing technology has uncovered the previously obscure molecular mechanisms, providing clues for better stratification of patients and identification of druggable targets for the disease. Identification of active oncogenic pathways and gene-gene interactions may reveal oncogene addiction and synthetic lethality. Relevant findings can be extrapolated to develop targeted and personalized therapeutic interventions. In addition to known mutational events, the role of chromosomal rearrangements in pancreatic neoplasms is gradually uncovered. Coupled with bioinformatics pipelines and epidemiological analyses, a better framework for risk stratification and prognostication of pancreatic cancer will be possible in the near future. In this review, we discuss how translational genomic studies facilitate our understanding of pathobiology, and development of novel diagnostics and therapeutics for pancreatic ductal adenocarcinoma with emphases on whole genome sequencing, whole exome sequencing, and liquid biopsies. We have also re-analyzed The Cancer Genome Atlas (TCGA) dataset to look for genetic features associated with altered survival in patients with pancreatic ductal adenocarcinoma.