Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity

Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies

Molecular markers and potential therapeutic targets in non-WNT/non-SHH (group 3 and group 4) medulloblastomas

Childhood medulloblastomas (MB) are heterogeneous and are divided into four molecular subgroups. The provisional non-wingless-activated (WNT)/non-sonic hedgehog-activated (SHH) category combining group 3 and group 4 represents over two thirds of all MBs, coupled with the highest rates of metastases and least understood pathology. The molecular era expanded our knowledge about molecular aberrations involved in MB tumorigenesis, and here, we review processes leading to non-WNT/non-SHH MB formations.The heterogeneous group 3 and group 4 MBs frequently harbor rare individual genetic alterations, yet the emerging profiles suggest that infrequent events converge on common, potentially targetable signaling pathways. A mutual theme is the altered epigenetic regulation, and in vitro approaches targeting epigenetic machinery are promising. Growing evidence indicates the presence of an intermediate, mixed signature group along group 3 and group 4, and future clarifications are imperative for concordant classification, as misidentifying patient samples has serious implications for therapy and clinical trials.To subdue the high MB mortality, we need to discern mechanisms of disease spread and recurrence. Current preclinical models do not represent the full scale of group 3 and group 4 heterogeneity: all of existing group 3 cell lines are MYC-amplified and most mouse models resemble MYC-activated MBs. Clinical samples provide a wealth of information about the genetic divergence between primary tumors and metastatic clones, but recurrent MBs are rarely resected. Molecularly stratified treatment options are limited, and targeted therapies are still in preclinical development. Attacking these aggressive tumors at multiple frontiers will be needed to improve stagnant survival rates

Increased frequency of single base substitutions in a population of transcripts expressed in cancer cells

<p>Abstract</p> <p>Background</p> <p>Single Base Substitutions (SBS) that alter transcripts expressed in cancer originate from somatic mutations. However, recent studies report SBS in transcripts that are not supported by the genomic DNA of tumor cells.</p> <p>Methods</p> <p>We used sequence based whole genome expression profiling, namely Long-SAGE (L-SAGE) and Tag-seq (a combination of L-SAGE and deep sequencing), and computational methods to identify transcripts with greater SBS frequencies in cancer. Millions of tags produced by 40 healthy and 47 cancer L-SAGE experiments were compared to 1,959 Reference Tags (RT), i.e. tags matching the human genome exactly once. Similarly, tens of millions of tags produced by 7 healthy and 8 cancer Tag-seq experiments were compared to 8,572 RT. For each transcript, SBS frequencies in healthy and cancer cells were statistically tested for equality.</p> <p>Results</p> <p>In the L-SAGE and Tag-seq experiments, 372 and 4,289 transcripts respectively, showed greater SBS frequencies in cancer. Increased SBS frequencies could not be attributed to known Single Nucleotide Polymorphisms (SNP), catalogued somatic mutations or RNA-editing enzymes. Hypothesizing that Single Tags (ST), i.e. tags sequenced only once, were indicators of SBS, we observed that ST proportions were heterogeneously distributed across Embryonic Stem Cells (ESC), healthy differentiated and cancer cells. ESC had the lowest ST proportions, whereas cancer cells had the greatest. Finally, in a series of experiments carried out on a single patient at 1 healthy and 3 consecutive tumor stages, we could show that SBS frequencies increased during cancer progression.</p> <p>Conclusion</p> <p>If the mechanisms generating the base substitutions could be known, increased SBS frequency in transcripts would be a new useful biomarker of cancer. With the reduction of sequencing cost, sequence based whole genome expression profiling could be used to characterize increased SBS frequency in patient’s tumor and aid diagnostic.</p