Connecting chemosensitivity, gene expression and disease

Immuno-PET imaging for non-invasive assessment of cetuximab accumulation in non-small cell lung cancer

Backgrounds

Overexpression of epidermal growth factor receptor (EGFR) has been established as a valid therapeutic target of non-small cell lung cancer (NSCLC). However, the clinical benefit of cetuximab as an EGFR-targeting drug is still controversial, partially due to the lack of effective means to identify suitable patients. This study aimed to investigate the potential of radiolabeled cetuximab as a non-invasive tool to predict cetuximab accumulation in NSCLC tumor xenografts with varying EGFR expression levels.

Methods

The NSCLC tumors in model mice were subjected to in vivo biodistribution study and positron emission tomography (PET) imaging 48 h after injection of either ¹¹¹In- or ⁶⁴Cu-labeled cetuximab. The EGFR expression levels of NSCLC tumors were determined by ex vivo immunoblotting.

Results

We found that tumors with high EGFR expression had significantly higher [¹¹¹In]In-DOTA-cetuximab accumulation than tumors with moderate to low EGFR expression (P < 0.05). Strong correlations were found between [¹¹¹In]In-DOTA-cetuximab tumor uptake and EGFR expression level (r = 0.893), and between [⁶⁴Cu]Cu-DOTA-cetuximab tumor uptake with EGFR expression level (r = 0.915). PET imaging with [⁶⁴Cu]Cu-DOTA-cetuximab allowed clear visualization of tumors.

Conclusion

Our findings suggest that this immuno-PET imaging can be clinically translated as a tool to predict cetuximab accumulation in NSCLC cancer patients prior to cetuximab therapy.

Using drug response data to identify molecular effectors, and molecular "omic" data to identify candidate drugs in cancer

The current convergence of molecular and pharmacological data provides unprecedented opportunities to gain insights into the relationships between the two types of data. Multiple forms of large-scale molecular data, including but not limited to gene and microRNA transcript expression, DNA somatic and germline variations from next-generation DNA and RNA sequencing, and DNA copy number from array comparative genomic hybridization are all potentially informative when one attempts to recognize the panoply of potentially influential events both for cancer progression and therapeutic outcome. Concurrently, there has also been a substantial expansion of the pharmacological data being accrued in a systematic fashion. For cancer cell lines, the National Cancer Institute cell line panel (NCI-60), the Cancer Cell Line Encyclopedia (CCLE), and the collaborative Genomics of Drug Sensitivity in Cancer (GDSC) databases all provide subsets of these forms of data. For the patient-derived data, The Cancer Genome Atlas (TCGA) provides analogous forms of genomic information along with treatment histories. Integration of these data in turn relies on the fields of statistics and statistical learning. Multiple algorithmic approaches may be chosen, depending on the data being considered, and the nature of the question being asked. Combining these algorithms with prior biological knowledge, the results of molecular biological studies, and the consideration of genes as pathways or functional groups provides both the challenge and the potential of the field. The ultimate goal is to provide a paradigm shift in the way that drugs are selected to provide a more targeted and efficacious outcome for the patient.

Prediction of drug efficacy for cancer treatment based on comparative analysis of chemosensitivity and gene expression data

The NCI60 database is the largest available collection of compounds with measured anti-cancer activity. The strengths and limitations for using the NCI60 database as a source of new anti-cancer agents are explored and discussed in relation to previous studies. We selected a sub-set of 2333 compounds with reliable experimental half maximum growth inhibitions (GI(50)) values for 30 cell lines from the NCI60 data set and evaluated their growth inhibitory effect (chemosensitivity) with respect to tissue of origin. This was done by identifying natural clusters in the chemosensitivity data set and in a data set of expression profiles of 1901 genes for the corresponding tumor cell lines. Five clusters were identified based on the gene expression data using self-organizing maps (SOM), comprising leukemia, melanoma, ovarian and prostate, basal breast, and luminal breast cancer cells, respectively. The strong difference in gene expression between basal and luminal breast cancer cells was reflected clearly in the chemosensitivity data. Although most compounds in the data set were of low potency, high efficacy compounds that showed specificity with respect to tissue of origin could be found. Furthermore, eight potential topoisomerase II inhibitors were identified using a structural similarity search. Finally, a set of genes with expression profiles that were significantly correlated with anti-cancer drug activity was identified. Our study demonstrates that the combined data sets, which provide comprehensive information on drug activity and gene expression profiles of tumor cell lines studied, are useful for identifying potential new active compounds.

Predictive value of MTT assay as an in vitro chemosensitivity testing for gastric cancer: One institution’s experience

AIM: To investigate the predictive clinical value of in vitro 3-(4,5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide (MTT) assay for directing chemosensitivity in patients with gastric cancer.

METHODS: Results of a total of 353 consecutive patients with gastric cancer treated with MTT-directed chemotherapy or physician’s empirical chemotherapy from July 1997 to April 2003 were reviewed and analyzed retrospectively.

RESULTS: The overall 5-year survival rate of MTT-sensitive group (MSG) and control group (CG) was 47.5% and 45.1%, respectively. The results of subgroup analysis with Cox proportional-hazards model were favorable for the MSG-sensitive group. However, no statistically significant difference in survival rate was observed between the two groups.

CONCLUSION: Individualized chemotherapy based on in vitro MTT assay is beneficial, but needs to be confirmed by further randomized controlled trials.