Implications of genetic testing in the management of colorectal cancer

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

Pancreatic ductal adenocarcinoma (PDAC) is a tumor with an extremely poor prognosis, predominantly as a result of chemotherapy resistance and numerous somatic mutations. Consequently, PDAC is a prime candidate for the use of sequencing to identify causative mutations, facilitating subsequent administration of targeted therapy. In a feasibility study, we retrospectively assessed the therapeutic recommendations of a novel, evidence-based software that analyzes next-generation sequencing (NGS) data using a large panel of pharmacogenomic biomarkers for efficacy and toxicity. Tissue from 14 patients with PDAC was sequenced using NGS with a 620 gene panel. FASTQ files were fed into treatmentmap. The results were compared with chemotherapy in the patients, including all side effects. No changes in therapy were made. Known driver mutations for PDAC were confirmed (e.g. KRAS, TP53). Software analysis revealed positive biomarkers for predicted effective and ineffective treatments in all patients. At least one biomarker associated with increased toxicity could be detected in all patients. Patients had been receiving one of the currently approved chemotherapy agents. In two patients, toxicity could have been correctly predicted by the software analysis. The results suggest that NGS, in combination with an evidence-based software, could be conducted within a 2-week period, thus being feasible for clinical routine. Therapy recommendations were principally off-label use. Based on the predominant KRAS mutations, other drugs were predicted to be ineffective. The pharmacogenomic biomarkers indicative of increased toxicity could be retrospectively linked to reported negative side effects in the respective patients. Finally, the occurrence of somatic and germline mutations in cancer syndrome-associated genes is noteworthy, despite a high frequency of these particular variants in the background population. These results suggest software-analysis of NGS data provides evidence-based information on effective, ineffective and toxic drugs, potentially forming the basis for precision cancer medicine in PDAC.

[mRNA quantification. The next challenge in routine diagnostics]

The application of predictive biomarkers results in an increase in the response rates and overall survival of cancer patients. This had been shown impressively for the detection of mutations in the proto-oncogenes KRAS and EGFR for the application of anti-EGFR targeted therapies in metastatic colorectal carcinomas and non-small-cell lung cancer, respectively. This mutation detection is of a qualitative nature. In addition, predictive biomarkers are known for the use of the commonly administered chemotherapeutics 5-fluorouracil, platinum-containing complexes, and Irinotecan, which are normally identical to the targets of the therapeutic compounds. The determination of these predictive biomarkers also results in an increase in response rates and overall survival. However, this detection is done via the quantitative determination of mRNA expression levels, implying greater efforts in detection, knowledge of cut-off levels, and higher requirements for nationwide establishment.

Molecular inversion probe analysis of gene copy alterations reveals distinct categories of colorectal carcinoma

Genomic instability is a major feature of neoplastic development in colorectal carcinoma and other cancers. Specific genomic instability events, such as deletions in chromosomes and other alterations in gene copy number, have potential utility as biologically relevant prognostic biomarkers. For example, genomic deletions on chromosome arm 18q are an indicator of colorectal carcinoma behavior and potentially useful as a prognostic indicator. Adapting a novel genomic technology called molecular inversion probes which can determine gene copy alterations, such as genomic deletions, we designed a set of probes to interrogate several hundred individual exons of >200 cancer genes with an overall distribution covering all chromosome arms. In addition, >100 probes were designed in close proximity of microsatellite markers on chromosome arm 18q. We analyzed a set of colorectal carcinoma cell lines and primary colorectal tumor samples for gene copy alterations and deletion mutations in exons. Based on clustering analysis, we distinguished the different categories of genomic instability among the colorectal cancer cell lines. Our analysis of primary tumors uncovered several distinct categories of colorectal carcinoma, each with specific patterns of 18q deletions and deletion mutations in specific genes. This finding has potential clinical ramifications given the application of 18q loss of heterozygosity events as a potential indicator for adjuvant treatment in stage II colorectal carcinoma.

Common denominator genes that distinguish colorectal carcinoma from normal mucosa

PURPOSE

Microarray technology has been used by a growing number of investigators and several studies have been published that list hundreds of genes differentially expressed by colorectal carcinoma (CRC) and normal mucosa (MC). On the basis of our own and other investigators' microarray data, our goal was to identify a common denominator gene cluster distinguishing CRC from MC.

METHODS

Thirty GeneChips (HG-U133A, Affymetrix) were hybridized, 20 with RNA of CRC stages I-IV (UICC) and 10 with MC. Expression signals showing at least a 4-fold difference between CRC and MC (p<0.01) were identified as differentially expressed. In addition, in our integrative data analysis approach only those genes whose expression was altered simultaneously in at least 2 of 5 recently published studies were subjected to an unsupervised hierarchical cluster analysis.

RESULTS

We detected 168 up- and 283 down-regulated genes in CRC relative to MC. Twenty-three genes were filtered from the five articles reviewed. An unsupervised hierarchical cluster analysis of these 23 genes confirmed the high specificity of these genes to differentiate between CRC and MC in our microarray data.

CONCLUSIONS

Colorectal cancer and mucosa could be clearly separated by 23 genes selected for being differentially expressed more than once in a recent literature review. These genes represent a common denominator gene cluster that can be used to distinguish colorectal MC from CRC.

Cancer pharmacogenomics: powerful tools in cancer chemotherapy and drug development

Interindividual differences in tumor response and normal tissue toxicities are consistently observed with most chemotherapeutic agents or regimens. While many clinical variables have been associated with drug responses (e.g., age, gender, diet, drug-drug interactions), inherited variations in drug disposition (metabolism and transport) genes and drug target genes also likely contribute to the observed variability in cancer treatment outcome. Pharmacogenomic studies aim to elucidate the genetic bases for interindividual differences and to use such genetic information to predict the safety, toxicity, and/or efficacy of drugs. There exist several clinically relevant examples of the utility of pharmacogenomics that associate specific genetic polymorphisms in drug metabolizing enzymes (e.g., TPMT, UGT1A1, DPD), drug transporters (MDR1), and drug target enzymes (TS) with clinical outcomes in patients treated with commonly prescribed chemotherapy drugs, such as 5-fluorouracil and irinotecan (Camptosar; Pfizer Pharmaceuticals; New York, NY http://www.pfizer.com). Techniques to discover and evaluate the functional significance of these polymorphisms have evolved in recent years and may soon be applied to clinical practice and clinical trials of currently prescribed anticancer drugs as well as new therapeutic agents. This review discusses the current and future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.

Single nucleotide polymorphisms and outcome in docetaxel-cisplatin-treated advanced non-small-cell lung cancer

BACKGROUND

Platinum-based doublets are the standard chemotherapy for advanced non-small-cell lung cancer (NSCLC). Excision-repair cross-complementing 1 (ERCC1), xeroderma pigmentosum group D (XPD) and ribonucleotide reductase subunit M1 (RRM1) are essential to the repair of cisplatin DNA adducts. Multidrug resistance 1 (MDR1) has been related to antimicrotubule resistance. We assessed whether single nucleotide polymorphisms (SNPs) in ERCC1, XPD, RRM1 and MDR1, and ERCC1 mRNA expression, predicted survival in docetaxel-cisplatin-treated stage IV NSCLC patients.

PATIENTS AND METHODS

Using the TaqMan 5' nuclease assay, we examined ERCC1 118, XPD 751 and 312, RRM1 -37C/A, and MDR1 C3435T SNPs in peripheral blood lymphocytes (PBLs) obtained from 62 docetaxel-cisplatin-treated advanced NSCLC patients. ERCC1 expression was measured in RNA isolated from PBLs using real-time reverse transcriptase PCR.

RESULTS

Overall median survival was 10.26 months. Median survival was 9.67 months for 34 patients with ERCC1 118 C/T, 9.74 months for 17 patients with T/T, and not reached for 11 patients with C/C (P=0.04). Similar significant differences in time to progression were observed according to ERCC1 118 genotype (P=0.03). No other significant differences were observed.

CONCLUSIONS

Patients homozygous for the ERCC1 118 C allele demonstrated a significantly better survival. ERCC1 SNP assessment could be an important component of tailored chemotherapy trials.