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Supervised risk predictor of breast cancer based on intrinsic subtypes.

Posted on May 25, 2021April 29, 2021 by Leah

Designer deletion strains derived from Saccharomyces cerevisiae S288C: a useful set of strains and plasmids for PCR-mediated gene disruption and other applications.

A set of yeast strains based on Saccharomyces cerevisiae S288C in which commonly used selectable marker genes are deleted by design based on the yeast genome sequence has been constructed and analysed. These strains minimize or eliminate the homology to the corresponding marker genes in commonly used vectors without significantly affecting adjacent gene expression.
Because the homology between commonly used auxotrophic marker gene segments and genomic sequences has been largely or completely abolished, these strains will also reduce plasmid integration events which can interfere with a wide variety of molecular genetic applications. We also report the construction of new members of the pRS400 series of vectors, containing the kanMX, ADE2 and MET15 genes.

Supervised risk predictor of breast cancer based on intrinsic subtypes.

PURPOSE To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression-based “intrinsic” subtypes luminal A, luminal B, HER2-enriched, and basal-like. METHODS A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen.
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RESULTS
The intrinsic subtypes as discrete entities showed prognostic significance (P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for the combined model (subtype and tumor size) was a significant improvement on either the clinicopathologic model or subtype model alone.
The intrinsic subtype model predicted neoadjuvant chemotherapy efficacy with a negative predictive value for pCR of 97%. CONCLUSION Diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer. The prognostic properties of the continuous risk score will be of value for the management of node-negative breast cancers. The subtypes and risk score can also be used to assess the likelihood of efficacy from neoadjuvant chemotherapy.

Unique microRNA molecular profiles in lung cancer diagnosis and prognosis.

MicroRNA (miRNA) expression profiles for lung cancers were examined to investigate miRNA’s involvement in lung carcinogenesis. miRNA microarray analysis identified statistical unique profiles, which could discriminate lung cancers from noncancerous lung tissues as well as molecular signatures that differ in tumor histology. miRNA expression profiles correlated with survival of lung adenocarcinomas, including those classified as disease stage I.
High hsa-mir-155 and low hsa-let-7a-2 expression correlated with poor survival by univariate analysis as well as multivariate analysis for hsa-mir-155. The miRNA expression signature on outcome was confirmed by real-time RT-PCR analysis of precursor miRNAs and cross-validated with an independent set of adenocarcinomas. These results indicate that miRNA expression profiles are diagnostic and prognostic markers of lung cancer.

New heterologous modules for classical or PCR-based gene disruptions in Saccharomyces cerevisiae.

We have constructed and tested a dominant resistance module, for selection of S. cerevisiae transformants, which entirely consists of heterologous DNA. This kanMX module contains the known kanr open reading-frame of the E. coli transposon Tn903 fused to transcriptional and translational control sequences of the TEF gene of the filamentous fungus Ashbya gossypii. This hybrid module permits efficient selection of transformants resistant against geneticin (G418). We also constructed a lacZMT reporter module in which the open reading-frame of the E. coli lacZ gene (lacking the first 9 codons) is fused at its 3′ end to the S. cerevisiae ADH1 terminator. KanMX and the lacZMT module, or both modules together, were cloned in the center of a new multiple cloning sequence comprising 18 unique restriction sites flanked by Not I sites.
Using the double module for constructions of in-frame substitutions of genes, only one transformation experiment is necessary to test the activity of the promotor and to search for phenotypes due to inactivation of this gene. To allow for repeated use of the G418 selection some kanMX modules are flanked by 470 bp direct repeats, promoting in vivo excision with frequencies of 10(-3)-10(-4). The 1.4 kb kanMX module was also shown to be very useful for PCR based gene disruptions. In an experiment in which a gene disruption was done with DNA molecules carrying PCR-added terminal sequences of only 35 bases homology to each target site, all twelve tested geneticin-resistant colonies carried the correctly integrated kanMX module.

Real time quantitative PCR.

We have developed a novel “real time” quantitative PCR method. The method measures PCR product accumulation through a dual-labeled fluorogenic probe (i.e., TaqMan Probe). This method provides very accurate and reproducible quantitation of gene copies.
Unlike other quantitative PCR methods, real-time PCR does not require post-PCR sample handling, preventing potential PCR product carry-over contamination and resulting in much faster and higher throughput assays. The real-time PCR method has a very large dynamic range of starting target molecule determination (at least five orders of magnitude). Real-time quantitative PCR is extremely accurate and less labor-intensive than current quantitative PCR methods.

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