Shaolong Cao

Scientist at Biogen. Researcher in the field of bioinformatics/computational biology

[Wenyi Wang @WenyiWang4]

Thanks so much for your insightful questions and the report, Catherine!
Estimated Total Tumor mRNA Predicts Cancer Outcomes, Study Shows https://t.co/YGgB5KvMLl @GenomeWeb

[Shaolong Cao @ShaolongCao]

A great summary blog for our TmS paper - Tumor-specific total mRNA expression: a robust and prognostic feature across cancers https://t.co/Y732vSXHZv #

[Shaolong Cao @ShaolongCao]

We have developed a computational approach to quantify tumor-specific total mRNA levels from mixed tumor samples at scale. Special thanks to my advisor @WenyiWang4 and all wonderful team members and collaborators!

[Wenyi Wang @WenyiWang4]

Very excited to share our paper in Nature Biotechnology today! Huge amount of work by @ShaolongCao @sxj307 @JenniferWangMD et al! It is amazing to work with many experts across cancers. Every cancer tells its own story and our metric TmS can quantify it! https://t.co/7UiNTC745p

[Wenyi Wang @WenyiWang4]

Very excited to share our paper in Nature Biotechnology today! Huge amount of work by @ShaolongCao @sxj307 @JenniferWangMD et al! It is amazing to work with many experts across cancers. Every cancer tells its own story and our metric TmS can quantify it! https://t.co/7UiNTC745p

[Peter Van Loo @VanLooLab]

We’re looking for #postdocs interested in #cancergenomics to join our lab at @MDAndersonNews – An exciting opportunity to lead large-scale studies of #tumorevolution: https://t.co/qyOX63Tlua

[Maxime Tarabichi @MaxGalder]

Millions of extra mutations retrieved in the non-unique regions of cancer genomes!? In the coding sequence of known cancer genes? In immunoglobulin genes in lymphoid tumours? And members of intriguing gene families?
So thrilled this is finally out:
https://t.co/3zUsWReDsI
🥲🙃

[Wenyi Wang @WenyiWang4]

We found a robust feature of cancer cell plasticity in bulk tumors using TmS, a mixed-genome-adjusted transcriptome deconvolution metric. This feature has demonstrated molecular and clinical relevance across cancers (brief summary below).  Our preprint: https://t.co/VH5zIBseQQ.

[Wenyi Wang @WenyiWang4]

We released CliP v1.2 today for fast subclonal reconstruction. With further optimization in computation, CliP finished running on ~9500 TCGA samples within 1 hour, and demonstrated accuracy within matched PCAWG samples. https://t.co/Qmu61n8C6c. Great job! @yujie_jiang679 @sxj307

[Wenyi Wang @WenyiWang4]

(1/2) How much mRNA does a tumor cell produce and why does it matter? Our work led by @ShaolongCao and @JenniferWangMD finds that it’s an essential feature for tracking tumor phenotype. https://t.co/YdIMBzXkZp

[Shaolong Cao @ShaolongCao]

Also, while we are on the topic, get an ORCID; its free and its easy. This is especially important to disambiguate if you have a relatively common last name. (2/2)

[Shaolong Cao @ShaolongCao]

A tip I learned today: If you are on academic job market (or in academics) you should have a Google Scholar profile; you should make sure it is not a hot mess. Additional points for curated MyNCBI page (also should not be hot mess) In general, avoid hot messes. (1/2)

[Wenyi Wang @WenyiWang4]

Our paper reporting a new algorithm to predict de novo mutation probability, which found a ~50% DNM rate in TP53 is accepted by Genome Research! https://t.co/MhI7ErHXZJ. Thanks to our collaborators: @SharonSavageMD, @judygarber5, Louise, Kim, Val, Danielle, Kristin, and Phuong.😊

[Shaolong Cao @ShaolongCao]

Our lab is hiring postdocs

[Wenyi Wang @WenyiWang4]

I am hiring postdoctoral fellows who are interested in working on mathematical modeling to study tumor heterogeneity, evolution or cancer risk prediction with me. Please retweet. Thanks! 😊https://t.co/3PBBbtJIje

[Wenyi Wang @WenyiWang4]

I am hiring postdoctoral fellows who are interested in working on mathematical modeling to study tumor heterogeneity, evolution or cancer risk prediction with me. Please retweet. Thanks! 😊https://t.co/3PBBbtJIje

[Wenyi Wang @WenyiWang4]

My group developed a predictive model for calling de novo mutations in patients with inherited cancer syndromes, and found a higher rate of de novo TP53 mutation carriers than previously described. On bioRxiv: https://t.co/H9LtikU7Ta. Thanks for data! @SharonSavageMD @judygarber5

[Shaolong Cao @ShaolongCao]

Proud to be part of working group #pcawg

[Wenyi Wang @WenyiWang4]

I am proud to have worked on such an amazing project along with amazing researchers in the PCAWG tumor heterogeneity and evolution working group @VanLooLab @MoritzGerstung @quaidmorris @davidcwedge and other PCAWG working groups. #PanCancer #PCAWG

[Elissa Dodd-Eaton @ebdodd]

Excited to get our papers published in Cancer Research!

[Nature Portfolio @NaturePortfolio]

Whole-genome sequencing data for 2,778 cancer samples is used in a study in Nature to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades. https://t.co/pj75MmMnVc

[Cancer Research @CR_AACR]

Shin et al develop cancer-specific penetrance estimates for #LiFraumeni Syndrome (LFS) with the goal to better inform patients & improve risk management of healthy individuals from LFS families. @meganf1 @sharonsavagemd @WenyiWang4 @MDAndersonNews https://t.co/VJ8cdOh9gQ 1/2

[Wenyi Wang @WenyiWang4]

Cancer Research online today: Penetrance of different cancer types in families with Li-Fraumeni syndrome: a validation study using multi-center cohorts https://t.co/SWPAE3iM37