Bioinformatory-assisted analysis of next-generation sequencing data for precision medicine in pancreatic cancer

Pancreas 2000. My journey with the central organ

The European Pancreatic Club Lifetime Achievement Award is a distinction awarded for research on the pancreas and service to European Pancreatology. It comes with the obligation to submit a review article to our society's journal, Pancreatology. It was awarded to me 2023 and I take this opportunity to highlight my journey with the central organ AKA the pancreas, that is inseparatable from "Pancreas 2000" - an educational program for future pancreatologists, inaugurated by Karolinska Institutet.

Understanding the Genetic Landscape of Pancreatic Ductal Adenocarcinoma to Support Personalized Medicine: A Systematic Review

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. While population-wide screening recommendations for PDAC in asymptomatic individuals are not achievable due to its relatively low incidence, pancreatic cancer surveillance programs are recommended for patients with germline causative variants in PDAC susceptibility genes or a strong family history. In this study, we sought to determine the prevalence and significance of germline alterations in major genes (ATM, BRCA1, BRCA2, CDKN2A, EPCAM, MLH1, MSH2, MSH6, PALB2, PMS2, STK11, TP53) involved in PDAC susceptibility. We performed a systematic review of PubMed publications reporting germline variants identified in these genes in PDAC patients. Overall, the retrieved articles included 1493 PDAC patients. A high proportion of these patients (n = 1225/1493, 82%) were found to harbor alterations in genes (ATM, BRCA1, BRCA2, PALB2) involved in the homologous recombination repair (HRR) pathway. Specifically, the remaining PDAC patients were reported to carry alterations in genes playing a role in other cancer pathways (CDKN2A, STK11, TP53; n = 181/1493, 12.1%) or in the mismatch repair (MMR) pathway (MLH1, MSH2, MSH6, PMS2; n = 87/1493, 5.8%). Our findings highlight the importance of germline genetic characterization in PDAC patients for better personalized targeted therapies, clinical management, and surveillance.

CLCA4 and MS4A12 as the significant gene biomarkers of primary colorectal cancer

Background: Primary colorectal cancer (PCRC) is a common digestive tract cancer in the elderly. However, the treatment effect of PCRC is still limited, and the long-term survival rate is low. Therefore, further exploring the pathogenesis of PCRC, and searching for specific molecular targets for diagnosis are the development trends of precise medical treatment, which have important clinical significance.

Methods: The public data were downloaded from Gene Expression Omnibus (GEO) database. Verification for repeatability of intra-group data was performed by Pearson’s correlation test and principal component analysis. Differentially expressed genes (DEGs) between normal and PCRC were identified, and the protein–protein interaction (PPI) network was constructed. Significant module and hub genes were found in the PPI network. A total of 192 PCRC patients were recruited between 2010 and 2019 from the Fourth Hospital of Hebei Medical University. RT-PCR was used to measure the relative expression of CLCA4 and MS4A12. Furthermore, the study explored the effect of expression of CLCA4 and MS4A12 for overall survival.

Results: A total of 53 DEGs were identified between PCRC and normal colorectal tissues. Ten hub genes concerned to PCRC were screened, namely CLCA4, GUCA2A, GCG, SST, MS4A12, PLP1, CHGA, PYY, VIP, and GUCA2B. The PCRC patients with low expression of CLCA4 and MS4A12 has a worse overall survival than high expression of CLCA4 and MS4A12 (P<0.05).

Conclusion: The research of DEGs in PCRC (53 DEGs, 10 hub genes, especially CLCA4 and MS4A12) and related signaling pathways is conducive to the differential analysis of the molecular mechanism of PCRC.

Islets and pancreatic ductal adenocarcinoma - An opportunity for translational research from the 'Bench to the Bedside'

The islet-acinar axis is of prime importance to the optimal functioning of the human pancreas. Not only is this inter-relationship important for normal physiological processes, it is also relevant in diseased states, including chronic pancreatitis and pancreatic ductal adenocarcinoma (PDAC). Early experiments, nearly 4 decades ago, explored the role of islets in the development and progression of PDAC. These led to further studies that provided compelling evidence to support the role of islets and their hormones in PDAC. This association presents oncologists with therapeutic options not only for managing, but potentially preventing PDAC, a cancer that is well known for its poor patient outcomes. This review will discuss the accumulated evidence regarding the role of islets and their hormones in PDAC and highlight areas for future research.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Copy number of 8q24.3 drives HSF1 expression and patient outcome in cancer: an individual patient data meta-analysis

BACKGROUND

The heat-shock transcription factor 1 (HSF1) has been linked to cell proliferation and survival in cancer and has been proposed as a biomarker for poor prognosis. Here, we assessed the role of HSF1 expression in relation to copy number alteration (CNA) and cancer prognosis.

METHODS

Using 10,287 cancer genomes from The Cancer Genome Atlas and Cbioportal databases, we assessed the association of HSF1 expression with CNA and cancer prognosis. CNA of 8q24.3 was categorized as diploid (reference), deletion (fewer copies), gain (+ 1 copy) and amplification (≥ + 2 copies). Multivariate logistic regression modeling was used to assess 5-year survival among those with a first cancer diagnosis and complete follow-up data (N = 9568), categorized per anatomical location and histology, assessing interaction with tumor stage, and expressed as odds ratios and 95% confidence intervals.

RESULTS

We found that only 54.1% of all tumors have a normal predicted 8q24.3 copy number and that 8q24.3 located genes including HSF1 are mainly overexpressed due to increased copies number of 8q24.3 in different cancers. The tumor of patients having respectively gain (+ 1 copy) and amplification (≥ + 2 copies) of 8q24.3 display a global increase of 5-year mortality (odds ratio = 1.98, 95% CI 1.22-3.21) and (OR = 2.19, 1.13-4.26) after full adjustment. For separate cancer types, tumor patients with 8q24.3 deletion showed a marked increase of 5-year mortality in uterine (OR = 4.84, [2.75-8.51]), colorectal (OR = 4.12, [1.15-14.82]), and ovarian (OR = 1.83, [1.39-2.41]) cancers; and decreased mortality in kidney cancer (OR = 0.41, [0.21-0.82]). Gain of 8q24.3 resulted in significant mortality changes in 5-year mortality for cancer of the uterus (OR = 3.67, [2.03-6.66]), lung (OR = 1.76, [1.24-2.51]), colorectal (OR = 1.75, [1.32-2.31]) cancers; and amplification for uterine (OR = 4.58, [1.43-14.65]), prostate (OR = 4.41 [3.41-5.71]), head and neck (OR = 2.68, [2.17-3.30]), and stomach (OR = 0.56, [0.36-0.87]) cancers.

CONCLUSIONS

Here, we show that CNAs of 8q24.3 genes, including HSF1, are tightly linked to 8q24.3 copy number in tumor patients and can affect patient outcome. Our results indicate that the integration of 8q24.3 CNA detection may be a useful predictor for cancer prognosis.

Identification of Key Genes and Pathways in Pancreatic Cancer Gene Expression Profile by Integrative Analysis

Background: Pancreatic cancer is one of the malignant tumors that threaten human health. Methods: The gene expression profiles of GSE15471, GSE19650, GSE32676 and GSE71989 were downloaded from the gene expression omnibus database including pancreatic cancer and normal samples. The differentially expressed genes between the two types of samples were identified with the Limma package using R language. The gene ontology functional and pathway enrichment analyses of differentially-expressed genes were performed by the DAVID software followed by the construction of a protein–protein interaction network. Hub gene identification was performed by the plug-in cytoHubba in cytoscape software, and the reliability and survival analysis of hub genes was carried out in The Cancer Genome Atlas gene expression data. Results: The 138 differentially expressed genes were significantly enriched in biological processes including cell migration, cell adhesion and several pathways, mainly associated with extracellular matrix-receptor interaction and focal adhesion pathway in pancreatic cancer. The top hub genes, namely thrombospondin 1, DNA topoisomerase II alpha, syndecan 1, maternal embryonic leucine zipper kinase and proto-oncogene receptor tyrosine kinase Met were identified from the protein–protein interaction network. The expression levels of hub genes were consistent with data obtained in The Cancer Genome Atlas. DNA topoisomerase II alpha, syndecan 1, maternal embryonic leucine zipper kinase and proto-oncogene receptor tyrosine kinase Met were significantly linked with poor survival in pancreatic adenocarcinoma. Conclusions: These hub genes may be used as potential targets for pancreatic cancer diagnosis and treatment.

Next-Generation Sequencing in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is lethal, and the majority of patients present with locally advanced or metastatic disease that is not amenable to cure. Thus, with surgical resection being the only curative modality, it is critical that disease is identified at an earlier stage to allow the appropriate therapy to be applied. Unfortunately, a specific biomarker for early diagnosis has not yet been identified; hence, no screening process exists. Recently, high-throughput screening and next-generation sequencing (NGS) have led to the identification of novel biomarkers for many disease processes, and work has commenced in PDAC. Genomic data generated by NGS not only have the potential to assist clinicians in early diagnosis and screening, especially in high-risk populations, but also may eventually allow the development of personalized treatment programs with targeted therapies, given the large number of gene mutations seen in PDAC. This review introduces the basic concepts of NGS and provides a comprehensive review of the current understanding of genetics in PDAC as related to discoveries made using NGS.

Smyd2 conformational changes in response to p53 binding: role of the C-terminal domain

Smyd2 lysine methyltransferase regulates monomethylation of histone and nonhistone lysine residues using S‐adenosylmethionine cofactor as the methyl donor. The nonhistone interactors include several tumorigenic targets, including p53. Understanding this interaction would allow the structural principles that underpin Smyd2‐mediated p53 methylation to be elucidated. Here, we performed μ‐second molecular dynamics (MD) simulations on binary Smyd2‐cofactor and ternary Smyd2‐cofactor‐p53 peptide complexes. We considered both unmethylated and monomethylated p53 peptides (at Lys370 and Lys372). The results indicate that (a) the degree of conformational freedom of the C‐terminal domain of Smyd2 is restricted by the presence of the p53 peptide substrate, (b) the Smyd2 C‐terminal domain shows distinct dynamic properties when interacting with unmethylated and methylated p53 peptides, and (c) Lys372 methylation confines the p53 peptide conformation, with detectable influence on Lys370 accessibility to the cofactor. These MD results are therefore of relevance for studying the biology of p53 in cancer progression.

An Integrative Data Mining and Omics-Based Translational Model for the Identification and Validation of Oncogenic Biomarkers of Pancreatic Cancer

Substantial alterations at the multi-omics level of pancreatic cancer (PC) impede the possibility to diagnose and treat patients in early stages. Herein, we conducted an integrative omics-based translational analysis, utilizing next-generation sequencing, transcriptome meta-analysis, and immunohistochemistry, combined with statistical learning, to validate multiplex biomarker candidates for the diagnosis, prognosis, and management of PC. Experiment-based validation was conducted and supportive evidence for the essentiality of the candidates in PC were found at gene expression or protein level by practical biochemical methods. Remarkably, the random forests (RF) model exhibited an excellent diagnostic performance and LAMC2, ANXA2, ADAM9, and APLP2 greatly influenced its decisions. An explanation approach for the RF model was successfully constructed. Moreover, protein expression of LAMC2, ANXA2, ADAM9, and APLP2 was found correlated and significantly higher in PC patients in independent cohorts. Survival analysis revealed that patients with high expression of ADAM9 (Hazard ratio (HR)_OS = 2.2, p-value < 0.001), ANXA2 (HR_OS = 2.1, p-value < 0.001), and LAMC2 (HR_DFS = 1.8, p-value = 0.012) exhibited poorer survival rates. In conclusion, we successfully explore hidden biological insights from large-scale omics data and suggest that LAMC2, ANXA2, ADAM9, and APLP2 are robust biomarkers for early diagnosis, prognosis, and management for PC.

Engineering Precision Medicine

Advances in genomic sequencing and bioinformatics have led to the prospect of precision medicine where therapeutics can be advised by the genetic background of individuals. For example, mapping cancer genomics has revealed numerous genes that affect the therapeutic outcome of a drug. Through materials and cell engineering, many opportunities exist for engineers to contribute to precision medicine, such as engineering biosensors for diagnosis and health status monitoring, developing smart formulations for the controlled release of drugs, programming immune cells for targeted cancer therapy, differentiating pluripotent stem cells into desired lineages, fabricating bioscaffolds that support cell growth, or constructing "organs-on-chips" that can screen the effects of drugs. Collective engineering efforts will help transform precision medicine into a more personalized and effective healthcare approach. As continuous progress is made in engineering techniques, more tools will be available to fully realize precision medicine's potential.

Genomic testing for pancreatic cancer in clinical practice as real-world evidence

BACKGROUND

Precision medicine guided by comprehensive genome sequencing represents a potential treatment strategy for pancreatic cancer. However, clinical sequencing for pancreatic cancer entails several practical difficulties. We have launched an in-house clinical sequencing system and started genomic testing for patients with cancer in clinical practice. We have analyzed the clinical utility of this system in pancreatic cancer.

METHODS

We retrospectively reviewed 20 patients with pancreatic cancer who visited our division. Genomic DNA was extracted from both tumor tissue and peripheral blood mononuclear cells obtained from the patients. We performed a comprehensive genomic testing using targeted amplicon sequencing for 160 cancer-related genes. The primary endpoints were the detection rates of potential actionable and druggable gene alterations. The secondary endpoints were the detection rate of secondary germline findings, the rate of re-biopsy required for genome sequencing, survival time after the initial visit (post-sequencing survival time), and turnaround time.

RESULTS

Although re-biopsy was required for 25% (5/20) of all patients, genomic testing was performed in all patients. Actionable and druggable gene alterations were detected in 100% (20/20) and 35% (7/20) of patients, respectively, whereas secondary germline findings were detected in 5% (1/20) of patients. The median turnaround times for physicians and patients were 20 and 26 days, respectively. The median post-sequencing survival time was 10.3 months. Only 10% (2/20) of all patients were treated with therapeutic agents based on the outcomes of genomic testing.

CONCLUSIONS

The clinical application of comprehensive genomic testing for pancreatic cancer was feasible and promising in clinical practice.

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.

Novel biomarkers and endoscopic techniques for diagnosing pancreaticobiliary malignancy

The UK incidence of pancreatic ductal adenocarcinoma is 9 per 100,000 population, and biliary tract cancer occurs at a rate of 1–2 per 100,000. The incidence of both cancers is increasing annually and these tumours continue to be diagnosed late and at an advanced stage, limiting options for curative treatment. Population-based screening programmes do not exist for these cancers, and diagnosis currently is dependent on symptom recognition, but often symptoms are not present until the disease is advanced. Recently, a number of promising blood and urine biomarkers have been described for pancreaticobiliary malignancy and are summarised in this review. Novel endoscopic techniques such as single-operator cholangioscopy and confocal endomicroscopy have been used in some centres to enhance standard endoscopic diagnostic techniques and are also evaluated in this review.