Remodeling of Metastatic Vasculature Reduces Lung Colonization and Sensitizes Overt Metastases to Immunotherapy

Due to limited current therapies, metastases are the primary cause of mortality in cancer patients. Here, we employ a fusion compound of the cytokine LIGHT and a vascular targeting peptide (LIGHT-VTP) that homes to angiogenic blood vessels in primary tumors. We show in primary mouse lung cancer that normalization of tumor vasculature by LIGHT-VTP prevents cancer cell intravasation. Further, LIGHT-VTP efficiently targets pathological blood vessels in the pre-metastatic niche, reducing vascular hyper-permeability and extracellular matrix (ECM) deposition, thus blocking metastatic lung colonization. Moreover, we demonstrate that mouse and human metastatic melanoma deposits are targetable by VTP.

[Drug reverts leaky blood vessels to normal, preventing colonization by passing metastatic cancer cells. Also opposes primary tumors forming new blood vessels and suppresses their growth.]

More at: https://www.cell.com/cell-reports/fulltext/S2211-1247(19)31662-6

This is a BIG research.

Whole tumor genomes across cancers

This impressively large project, comprising many working groups focusing on various molecular or genetic features of cancer, has generated valuable data for the cancer research community that will continue to be mined for many years to come.

https://www.nature.com/articles/s41588-020-0597-2

Bacterial DNA signatures in blood point to new universal cancer test

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Using data from The Cancer Genome Atlas, the researchers analyzed over 18,000 tumor samples, spanning 33 different types of cancer. Machine learning models were then trained to dig through the mass of data and determine unique microbial DNA signatures that could be linked to specific cancer types.

Not only were these models initially successful in detecting cancer types from microbial DNA signatures, but the results held strong even after the researchers eliminated stage III and IV cancers from the dataset. This suggests the microbial patterns are present in blood at the earliest stages of the disease. The final stage of the preliminary study was testing these microbial signatures in real-life conditions. A number of plasma samples were taken from prostate, lung and skin cancer patients. All the patients were suffering from stage III or higher cancers, and the cohort included a control group of plasma samples taken from cancer-free subjects.

etc.

More at https://newatlas.com/science/bacteria-dna-sig...od-universal-cancer-test/

Universal cancer blood test detects and locates 50 types of tumors

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The test uses a machine learning algorithm to search for specific chemical changes to DNA, called methylation patterns, that are associated with cancer. This is found in the form of cell-free DNA (cfDNA), which is shed into the bloodstream from many cells, including tumors. The researchers started by training a machine learning algorithm on over 3,000 blood samples in the Circulating Cell-free Genome Atlas (CCGA). Half of these had cancer – one of 50 different types – while the other half didn’t. Once the algorithm had learned what methylation patterns to look for, it was put to work on classifying a further 1,200 samples, of which half had cancer.

And sure enough, the new test was largely successful, becoming more accurate for later stages of cancer. It was able to detect 18 percent of stage I tumors, 43 percent of stage II, 81 percent of stage III and 93 percent of stage IV. It was also able to pinpoint which tissue the cancer originated in with an accuracy of 93 percent, and importantly the false positive rate was just 0.7 percent.

[. . .]

Much more at: https://newatlas.com/medical/ai-powered-unive...etection-location-cancer/