1/ Thrilled to share our latest breakthrough in #CancerResearch! We've developed a novel machine learning model to predict patient response to immunotherapy. 🧬💊🔬 #Immunotherapy #AI. biorxiv.org/content/10.110… 2/ We analyzed eight cohorts of 2881 ICB-treated patients across 18 solid tumor types, the largest dataset to date, examining diverse clinical, pathologic, and genomic features.

Is chromosomal and/or focal copy number alterations predictive of patients’ survival following immunotherapy across all cancer types?

We answer this in our latest preprint, which contradicts major recently published claims about this relationship. biorxiv.org/content/10.110… Various studies have shown that high tumor mutation burden (TMB) may predict response to immune checkpoint blockade, at least in some cancer types. However, identifying patients with low TMB that respond to cancer immunotherapy is an important open challenge.

Drug target identification is at the heart of drug development, and we’ve been working to change how it’s been done.

We present DeepTarget: a new computational tool to characterize a drug’s mechanism of action in-depth beyond its primary target. 🧰🧵👇
biorxiv.org/content/10.110… The traditional drug development pipeline selects drugs that induce the desired effect on a target of interest. At scale, this has resulted in a series of drugs with a partial & fragmented, or downright incorrect, mechanism of action (MOA).

We present a method to address this.

Proud to share this!
We demonstrate that CRISPR-Cas9 based genetic editing selects for pre-existing mutant forms of two cancer driver genes (KRAS and P53) across delivery methods, cell types & is dependent on the gene being edited.
🧵How did we do this?
nature.com/articles/s4146… Who did this? This was achieved via a truly synergistic effort. The computation part was done by @Sanjusinha7 & @cheng_ky @joo_sang_lee @theNCI and an enormous experimental effort from @KarinaoBarbosa led by @anideshpandelab @sbpdiscovery

📢 Excited to share with you our newest preprint!

We systematically identified CAR targets for repurposing in solid tumors via a pan-cancer single cell transcriptomics analysis. This work is led by @sanna_madan @theNCI @umdcs. 1/10

biorxiv.org/content/10.110… CAR T cell therapy is a powerful and promising tool for unleashing lasting immunity against tumors, and is currently being studied in a myriad of clinical trials for various blood and solid cancers. 2/10

Excited to share our new preprint identifying the immune determinants of the association between tumor mutational burden and immunotherapy response across cancer types. An effort lead by @neelamsinha05 @Sanjusinha7 🧵 1/13 biorxiv.org/content/10.110… Last year, FDA approved High-tumor mutation burden (defined as >10mut/Mb) as a biomarker for immune checkpoint inhibitor (ICI, Pembro) treatment for all solid tumor types. 2/13

Very excited to share our synthetic lethality based precision oncology approach via the tumor transcriptome (SELECT) @Cell
This effort is led by @joo_sang_lee @theNCI #PrecisionMedicine [1/n]
cell.com/cell/fulltext/… Current precision oncology mainly targets actionable mutations & has limited patient coverage. We present the first precision oncology framework that systematically guides cancer treatment based on *synthetic lethal* vulnerabilities identified via the tumor transcriptome.

Can we infer an individual’s tissue-specific expression from their whole blood transcriptome?
Hot off the Press & a summary of our effort is below!
advances.sciencemag.org/content/7/14/e…
with @hannenhalli & @KunWang331 Learning an individual’s tissue-specific gene expression can be invaluable guiding diagnosis & monitoring progression of a wide range of diseases. Unfortunately, for most tissues, the transcriptome cannot be obtained without invasive procedures.

Excited to share our preprint introducing the first pipeline to identify Cell type Specific Intracellular (CSI) microbes from single cell RNA-seq data. Here's a tweetorial summary. biorxiv.org/content/10.110… Multiple recent studies have pointed to the functional importance of tumor microbiome. One eg., is the case of Fusobacterium in primary & metastatic colon tumors, which drives tumorigenesis, influences response to chemotherapy & binds to multiple human immune inhibitory receptors

We present (preprint) an approach for identifying drug treatments modulating the expression of a key protein required for the SARS-CoV-2 virus entry – the ACE2 (angiotensin-converting enzyme 2) receptor. preprints.org/manuscript/202… Two weeks ago, Fang et al suggested that diabetes and hypertension patients treated with ACE-inhibitors & AR-blockers are at a higher risk for COVID-19 as these treatments may increase ACE2 expression.

In a promising step for cancer precision medicine, we devised a novel strategy that identifies genetic interactions and robustly predicts drug response, spanning 21 targeted therapies and 11 immunotherapy datasets across 10 different cancer types (1/9) bit.ly/38Pzn9m To predict treatment outcomes, we defined genetic interaction scores, which capture the likelihood of a given patient responding to a given drug. (2/9)

We present the first computational strategy leveraging genetic interactions successfully predicting patients response to many different targeted and immunotherapy treatments based on their tumors transcriptome. Sharing the details here- biorxiv.org/content/10.110… Current precision oncology is mainly performed by targeting actionable mutations & has a limited patient coverage. Here we present the first approach for systematically guiding patients treatment based on vulnerabilities identified across the whole exome.

We identified for the first time a selection of three cancer driver mutations (P53, KRAS and VHL) during CRISPR-Cas9 gene editing and chart a comprehensive gene-wise editing risk map in our new work out today. This series summarizes it 1/X biorxiv.org/content/biorxi… Recent reports in @NatureMedicine suggested that CRISPR-Cas9 gene editing induces a p53-dependent DNA damage response in primary cells, which may select for cells with oncogenic p53 mutations. These CRISPR-induced possible changes needs a systematic and thorough testing. 2/X