Evolutionary selection of alleles in the melanophilin gene that impacts on prostate organ function and cancer risk

Proteomics-Derived Biomarker Panel Facilitates Distinguishing Primary Lung Adenocarcinomas With Intestinal or Mucinous Differentiation From Lung Metastatic Colorectal Cancer

The diagnosis of primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) remains challenging due to the overlapping histomorphological, immunohistochemical (IHC), and genetic characteristics with lung metastatic colorectal cancer (lmCRC). This study aimed to explore the protein biomarkers that could distinguish between PAIM and lmCRC. To uncover differences between the two diseases, we used tandem mass tagging-based shotgun proteomics to characterize proteomes of formalin-fixed, paraffin-embedded tumor samples of PAIM (n = 22) and lmCRC (n = 17).Then three machine learning algorithms, namely support vector machine (SVM), random forest, and the Least Absolute Shrinkage and Selection Operator, were utilized to select protein features with diagnostic significance. These candidate proteins were further validated in an independent cohort (PAIM, n = 11; lmCRC, n = 19) by IHC to confirm their diagnostic performance. In total, 105 proteins out of 7871 proteins were significantly dysregulated between PAIM and lmCRC samples and well-separated two groups by Uniform Manifold Approximation and Projection. The upregulated proteins in PAIM were involved in actin cytoskeleton organization, platelet degranulation, and regulation of leukocyte chemotaxis, while downregulated ones were involved in mitochondrial transmembrane transport, vasculature development, and stem cell proliferation. A set of ten candidate proteins (high-level expression in lmCRC: CDH17, ATP1B3, GLB1, OXNAD1, LYST, FABP1; high-level expression in PAIM: CK7 (an established marker), NARR, MLPH, S100A14) was ultimately selected to distinguish PAIM from lmCRC by machine learning algorithms. We further confirmed using IHC that the five protein biomarkers including CDH17, CK7, MLPH, FABP1 and NARR were effective biomarkers for distinguishing PAIM from lmCRC. Our study depicts PAIM-specific proteomic characteristics and demonstrates the potential utility of new protein biomarkers for the differential diagnosis of PAIM and lmCRC. These findings may contribute to improving the diagnostic accuracy and guide appropriate treatments for these patients.

Melanophilin Polymorphism in Ferrets of Different Color

In mammals, the main contribution to the variability of pigmentation is made by two groups of genes directly related to the metabolic pathways of pigment synthesis and controlling the transport of melanosomes in melanocytes to keratinocytes. In order to identify the genetic basis of pigmentation variants, the nucleotide sequences of the melanophilin gene were compared in two groups of ferrets-silver-colored and wild-type animals-using sequencing of 16 exons. In carriers of silver color, a single nucleotide deletion was detected in the 9th exon, leading to a shift in the reading frame and the formation of a stop codon downstream. The protein encoded by the mutant allele is almost completely devoid of the C terminal domain of the protein responsible for the contact of melanosomes with actin during their moving to the periphery of melanocytes, but it retains the leading domain involved in the formation of melanosomes. The combination of the preservation of the N domain and the defect of the C domain of the mutant protein for the first time makes it possible to explain the incomplete dominance of the wild-type protein in heterozygotes.

The adaptive evolution of cancer driver genes

BACKGROUND

Cancer is a life-threatening disease in humans; yet, cancer genes are frequently reported to be under positive selection. This suggests an evolutionary-genetic paradox in which cancer evolves as a secondary product of selection in human beings. However, systematic investigation of the evolution of cancer driver genes is sparse.

RESULTS

Using comparative genomics analysis, population genetics analysis and computational molecular evolutionary analysis, the evolution of 568 cancer driver genes of 66 cancer types were evaluated at two levels, selection on the early evolution of humans (long timescale selection in the human lineage during primate evolution, i.e., millions of years), and recent selection in modern human populations (~ 100,000 years). Results showed that eight cancer genes covering 11 cancer types were under positive selection in the human lineage (long timescale selection). And 35 cancer genes covering 47 cancer types were under positive selection in modern human populations (recent selection). Moreover, SNPs associated with thyroid cancer in three thyroid cancer driver genes (CUX1, HERC2 and RGPD3) were under positive selection in East Asian and European populations, consistent with the high incidence of thyroid cancer in these populations.

CONCLUSIONS

These findings suggest that cancer can be evolved, in part, as a by-product of adaptive changes in humans. Different SNPs at the same locus can be under different selection pressures in different populations, and thus should be under consideration during precision medicine, especially for targeted medicine in specific populations.

FACS-Free isolation and purification protocol of mouse prostate epithelial cells for organoid primary culture

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This protocol enables the generation of mouse prostate organoids without using flow cytometry, facilitating its implementation in most research laboratories.

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Usage of prostate organoids allows the study of complex in vivo phenotypes, beyond what can be done with immortalized cell lines.

The prostate is a gland that contributes to men's fertility. It is highly responsive to androgens and is often the site of carcinogenesis, as prostate cancer is the most frequent cancer in men in over a hundred countries. To study the normal prostate, few in vitro models exist, and most of them do not express the androgen receptor (AR). To overcome this issue, prostate epithelial cells can be grown in primary culture ex vivo in 2- and 3-dimensional culture (organoids). However, methods to purify these cells often require flow cytometry, thus necessitating specialized instruments and expertise. Herein, we present a detailed protocol for the harvest, purification, and primary culture of mouse prostate epithelial cells to grow prostate organoids ex vivo. This protocol does not require flow cytometry approaches, facilitating its implementation in most research laboratories, and organoids grown with this protocol are highly responsive to androgens. In summary, we present a new simple method that can be used to grow prostate organoids that recapitulate the androgen response of this gland in vivo.