Targeting chaperonin containing TCP1 (CCT) as a molecular therapeutic for small cell lung cancer.

Identifying new druggable targets is desired to meet the needs for effective cancer treatments. To this end, we previously reported the efficacy of a therapeutic peptide called CT20p that displays selective cytotoxicity through inhibition of a multi-subunit, protein-folding complex called Chaperonin-Containing TCP-1 (CCT). To investigate the role of CCT in cancer progression, we examined protein levels of CCT subunits in liver, prostate, and lung cancer using human tissue microarrays. We found that these cancers expressed higher levels of CCT2 as compared to normal tissues. Small cell lung cancer (SCLC) stood out as having statistically significant difference in CCT2. Higher levels of CCT2 in tumors from lung cancer patients were also associated with decreased survival. Using SCLC cell lines, we observed detectable amounts of CCT subunits and cells were susceptible to killing by CT20p. Treatment with CT20p, delivered to cells using polymeric nanoparticles, was cytotoxic to all SCLC cell lines, decreasing the levels of CCT client proteins like STAT3. In contrast, treatment with a STAT3 inhibitor was effective in one of the SCLC cell lines. While we found that CCT levels could vary in cell lines, normal tissues had low levels of CCT and minimal toxicity to liver or kidney function was observed in mice treated with CT20p. These results indicate that in SCLC, changes in CCT levels could be used as a biomarker for diagnosis and that targeting CCT for inhibition with CT20p is a promising treatment approach for those cancers such as SCLC that currently lack targeted therapeutics.

Rapid depletion of target proteins allows identification of coincident physiological responses.

Targeted protein degradation is a powerful tool that can be used to create unique physiologies depleted of important factors. Current strategies involve modifying a gene of interest such that a degradation peptide is added to an expressed target protein and then conditionally activating proteolysis, either by expressing adapters, unmasking cryptic recognition determinants, or regulating protease affinities using small molecules. For each target, substantial optimization may be required to achieve a practical depletion, in that the target remains present at a normal level prior to induction and is then rapidly depleted to levels low enough to manifest a physiological response. Here, we describe a simplified targeted degradation system that rapidly depletes targets and that can be applied to a wide variety of proteins without optimizing target protease affinities. The depletion of the target is rapid enough that a primary physiological response manifests that is related to the function of the target. Using ribosomal protein S1 as an example, we show that the rapid depletion of this essential translation factor invokes concomitant changes to the levels of several mRNAs, even before appreciable cell division has occurred.

Robust quantification of polymerase chain reactions using global fitting.

BACKGROUND: Quantitative polymerase chain reactions (qPCR) are used to monitor relative changes in very small amounts of DNA. One drawback to qPCR is reproducibility: measuring the same sample multiple times can yield data that is so noisy that important differences can be dismissed. Numerous analytical methods have been employed that can extract the relative template abundance between samples. However, each method is sensitive to baseline assignment and to the unique shape profiles of individual reactions, which gives rise to increased variance stemming from the analytical procedure itself. PRINCIPAL FINDINGS: We developed a simple mathematical model that accurately describes the entire PCR reaction profile using only two reaction variables that depict the maximum capacity of the reaction and feedback inhibition. This model allows quantification that is more accurate than existing methods and takes advantage of the brighter fluorescence signals from later cycles. Because the model describes the entire reaction, the influences of baseline adjustment errors, reaction efficiencies, template abundance, and signal loss per cycle could be formalized. We determined that the common cycle-threshold method of data analysis introduces unnecessary variance because of inappropriate baseline adjustments, a dynamic reaction efficiency, and also a reliance on data with a low signal-to-noise ratio. SIGNIFICANCE: Using our model, fits to raw data can be used to determine template abundance with high precision, even when the data contains baseline and signal loss defects. This improvement reduces the time and cost associated with qPCR and should be applicable in a variety of academic, clinical, and biotechnological settings.