Prognostic Biomarkers for Pancreatic Ductal Adenocarcinoma: An Umbrella Review

Background: Pancreatic ductal adenocarcinoma (PDAC) leads to the majority of cancer-related deaths due to its morbidity with similar mortality. Lack of effective prognostic biomarkers are the main reason for belated post-operative intervention of recurrence which causes high mortality. Numerous systematic reviews and meta-analyses have explored the prognostic value of biomarkers in PDAC so far. In this article, we performed an umbrella review analyzing these studies to provide an overview of associations between prognostic biomarkers and PDAC survival outcome and synthesized these results to guide better clinical practice.

Methods: Systematic reviews and meta-analyses investigating the associations between PDAC survival outcomes and prognostic biomarkers were acquired via the PubMed and Embase databases from inception till February 1, 2020. Associations supported by nominally statistically significant results were classified into strong, highly suggestive, suggestive, and weak based on several critical factors such as the statistical significance of summary estimates, the number of events, the estimate of the largest study included, interstudy heterogeneity, small-study effects, 95% predictive interval (PI), excess significance bias, and the results of credibility ceiling sensitivity analyses.

Results: We included 41 meta-analyses containing 63 associations between PDAC survival outcomes and prognostic biomarkers. Although, none was supported by strong evidence among these associations, an association between C-reactive protein to albumin ratio (CAR) and PDAC overall survival (OS) and an association between neutrophil-lymphocyte ratio (NLR) and PDAC OS were supported by highly suggestive evidence. Otherwise, the association between lactate dehydrogenase (LDH) and PDAC OS was supported by suggestive evidence. The remaining 60 associations were supported by weak or not suggestive evidence.

Conclusion: Associations between CAR or NLR and PDAC OS were supported by highly suggestive evidence. And the association between LDH and PDAC OS was supported by suggestive evidence. Although the methodological quality of the included systematic reviews and meta-analyses which were evaluated by AMSTAR2.0 is generally poor, the identification of the relatively robust prognostic biomarkers of PDAC may guide better post-operative intervention and follow-up to prolong patients' survival.

Prognostic Implications of Expression Profiling for Gemcitabine-Related Genes (hENT1, dCK, RRM1, RRM2) in Patients With Resectable Pancreatic Adenocarcinoma Receiving Adjuvant Chemotherapy

OBJECTIVES

The aim of this study was to examine the relevance of expression profiling of 4 genes involved in the action of gemcitabine among patients with pancreatic ductal-cell adenocarcinoma (PDAC).

METHODS

A group of 100 patients who underwent pancreatic resections for PDAC and received adjuvant chemotherapy with gemcitabine between 2007 and 2010 was identified. Expression of mRNAs for human equilibrative nucleoside transporter 1 (hENT1), ribonucleotide reductase subunits (RRM1, RRM2), and deoxycytidine kinase (dCK) was examined by quantitative real-time polymerase chain reaction, normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and dichotomized into groups of low and moderate/high expression levels grouped by tertiles.

RESULTS

Significantly better median survival times were found for high/moderate expression levels of hENT1 (27.9 vs 12.4 months, P = 0.001) and dCK (19.7 vs 10.5 months, P = 0.003), as well as low expression of RRM1 (23.4 vs 11.4 months, P = 0.027). A Cox proportional hazards model identified low expression of hENT1 (hazard ratio [HR], 3.38; 95% confidence intervals [CI], 2.28-10.50) and dCK (HR, 2.24; 95% CI, 1.63-3.39), and high/moderate levels of RRM1 (HR, 1.65; 95% CI, 1.23-2.45) as negative prognostic factors.

CONCLUSIONS

Expression of hENT, RRM1, and dCK genes provides important prognostic information for PDAC patients treated with adjuvant gemcitabine.

Personalized medicine in sporadic pancreatic cancer without homologous recombination-deficiency: are we any closer?

Pancreatic adenocarcinoma is the fourth leading cause of cancer related death in the United States. Most patients are diagnosed at a late stage and despite recent advances in chemotherapeutic approaches, outcomes are poor. With the introduction of combination chemotherapy, novel biomarkers are clearly needed to identify subsets of patients likely to benefit from these therapies. Advances in our understanding of the molecular drivers of pancreatic cancer offer the hope of personalized therapy that may benefit our patients. In this review, we summarize the current knowledge about the biology of pancreatic cancer and its implication for treatment. We discuss recent advances in targeted therapies and the role of potential biomarkers in predicting response to established therapies. We also review novel therapeutic approaches that may be able to fulfill the promise of personalized therapy for pancreatic cancer.

Integrative meta-analysis of multiple gene expression profiles in acquired gemcitabine-resistant cancer cell lines to identify novel therapeutic biomarkers

In molecular-targeted cancer therapy, acquired resistance to gemcitabine is a major clinical problem that reduces its effectiveness, resulting in recurrence and metastasis of cancers. In spite of great efforts to reveal the overall mechanism of acquired gemcitabine resistance, no definitive genetic factors have been identified that are absolutely responsible for the resistance process. Therefore, we performed a cross-platform meta-analysis of three publically available microarray datasets for cancer cell lines with acquired gemcitabine resistance, using the R-based RankProd algorithm, and were able to identify a total of 158 differentially expressed genes (DEGs; 76 up- and 82 down-regulated) that are potentially involved in acquired resistance to gemcitabine. Indeed, the top 20 up- and down-regulated DEGs are largely associated with a common process of carcinogenesis in many cells. For the top 50 up- and down-regulated DEGs, we conducted integrated analyses of a gene regulatory network, a gene co-expression network, and a protein-protein interaction network. The identified DEGs were functionally enriched via Gene Ontology hierarchy and Kyoto Encyclopedia of Genes and Genomes pathway analyses. By systemic combinational analysis of the three molecular networks, we could condense the total number of DEGs to final seven genes. Notably, GJA1, LEF1, and CCND2 were contained within the lists of the top 20 up- or down-regulated DEGs. Our study represents a comprehensive overview of the gene expression patterns associated with acquired gemcitabine resistance and theoretical support for further clinical therapeutic studies.

The Cancer Genomics Resource List 2014

CONTEXT

Genomic sequencing for cancer is offered by commercial for-profit laboratories, independent laboratory networks, and laboratories in academic medical centers and integrated health networks. The variability among the tests has created a complex, confusing environment.

OBJECTIVE

To address the complexity, the Personalized Health Care (PHC) Committee of the College of American Pathologists proposed the development of a cancer genomics resource list (CGRL). The goal of this resource was to assist the laboratory pathology and clinical oncology communities.

DESIGN

The PHC Committee established a working group in 2012 to address this goal. The group consisted of site-specific experts in cancer genetic sequencing. The group identified current next-generation sequencing (NGS)-based cancer tests and compiled them into a usable resource. The genes were annotated by the working group. The annotation process drew on published knowledge, including public databases and the medical literature.

RESULTS

The compiled list includes NGS panels offered by 19 laboratories or vendors, accompanied by annotations. The list has 611 different genes for which NGS-based mutation testing is offered. Surprisingly, of these 611 genes, 0 genes were listed in every panel, 43 genes were listed in 4 panels, and 54 genes were listed in 3 panels. In addition, tests for 393 genes were offered by only 1 or 2 institutions. Table 1 provides an example of gene mutations offered for breast cancer genomic testing with the annotation as it appears in the CGRL 2014.

CONCLUSIONS

The final product, referred to as the Cancer Genomics Resource List 2014, is available as supplemental digital content.

Association of GSTP1 and RRM1 Polymorphisms with the Response and Toxicity of Gemcitabine-cisplatin Combination Chemotherapy in Chinese Patients with Non-small Cell Lung Cancer

BACKGROUND

Previous studies showed that genetic polymorphisms of glutathione S-transferase P1 (GSTP1) were involved in glutathione metabolism and genetic polymorphisms of ribonucleotide reductase (RRM1) were correlated with DNA synthesis. Here we explored the effects of these polymorphisms on the chemosensitivity and clinical outcome in Chinese non-small cell lung cancer (NSCLC) patients treated with gemcitabine-cisplatin regimens.

MATERIALS AND METHODS

DNA sequencing was used to evaluate genetic polymorphisms of GSTP1 Ile105Val and RRM1 C37A-T524C in 47 NSCLC patients treated with gemcitabine-cisplatin regimens. Clinical response was evaluated according to RECIST criteria after 2 cycles of chemotherapy and toxicity was assessed by 1979 WHO criteria (acute and subacute toxicity graduation criteria in chemotherapeutic agents).

RESULTS

There was no statistical significance between sensitive and non-sensitive groups regarding the genotype frequency distribution of GSTP1 Ile105Val polymorphism (p>0.05). But for RRM1 C37A-T524C genotype, sensitive group had higher proportion of high effective genotype than non-sensitive group (p=0.009). And according to the joint detection of GSTP1 Ile105Val and RRM1 C37A-T524C polymorphisms, the proportion of type A (A/A+high effective genotype) was significantly higher in sensitive group than in non-sensitive group (p=0.009). Toxicity showed no correlation with the genotypes between two groups (p>0.05).

CONCLUSIONS

Compared with single detection of genetic polymorphisms of GSTP1 Ile105Val or RRM1 C37A-T524C, joint detection of both may be more helpful for patients with NSCLC to receive gemcitabine-cisplatin regimens as the first-line chemotherapy. Especially, genetic polymorphism of RRM1 is more likely to be used as an important biomarker to predict the response and toxicity of gemcitabine-cisplatin combination chemotherapy in NSCLC.