Fanying Tang (@fanyingtang) 's Twitter Profile
Fanying Tang

@fanyingtang

ID: 893568291725340672

calendar_today04-08-2017 20:24:17

2,2K Tweet

270 Followers

1,1K Following

Faisal Mahmood (@ai4pathology) 's Twitter Profile Photo

What would you do with 1000+ spatial transcriptomics samples with corresponding H&E-stained whole-slide images? Meet HEST-1k, a collection of 1,108 ST samples assembled from 131 public and internal cohorts encompassing 25 organs, 2 species. HEST-1k includes over 1.5 million

What would you do with 1000+ spatial transcriptomics samples with corresponding H&E-stained whole-slide images? Meet HEST-1k, a collection of 1,108 ST samples assembled from 131 public and internal cohorts encompassing 25 organs, 2 species. HEST-1k includes over 1.5 million
Fanying Tang (@fanyingtang) 's Twitter Profile Photo

Academic and industry folks, I’ll attend AACR in Chicago this year. Would love to catch up if you’re around and see what new things have emerged in #prostate cancer #RWE #RLT

Cancer Cell (@cancer_cell) 's Twitter Profile Photo

Online Now: Circular RMST cooperates with lineage-driving transcription factors to govern neuroendocrine transdifferentiation dlvr.it/TKJf0T

Online Now: Circular RMST cooperates with lineage-driving transcription factors to govern neuroendocrine transdifferentiation dlvr.it/TKJf0T
Jindan Yu (@yu_jindan) 's Twitter Profile Photo

Super exciting to see our first publication, led by talented postdoc Dr. Zhao in 2012, has led to something that will soon benefit patients! EZH2 and AR cooperate to repress tumor suppressors, which can be rescued by their inhibitor combo to suppress prostate cancer, per Pfizer Inc.!

Super exciting to see our first publication, led by talented postdoc Dr. Zhao in 2012, has led to something that will soon benefit patients! EZH2 and AR cooperate to repress tumor suppressors, which can be rescued by their inhibitor combo to suppress prostate cancer, per <a href="/pfizer/">Pfizer Inc.</a>!
Yüksel Ürün (@dryukselurun) 's Twitter Profile Photo

🔬Not just mutations. 🧬Not just methylation. The new frontier in early cancer detection? The cfDNA fragmentome—size, shape, structure, and silence. nature International Society of Liquid Biopsy OncoAlert doi.org/10.1038/s41568…

🔬Not just mutations.
🧬Not just methylation.
The new frontier in early cancer detection?
 The cfDNA fragmentome—size, shape, structure, and silence.
<a href="/Nature/">nature</a> <a href="/isliquidbiopsy/">International Society of Liquid Biopsy</a> <a href="/OncoAlert/">OncoAlert</a> 
doi.org/10.1038/s41568…
Chris Mason (@mason_lab) 's Twitter Profile Photo

Spatial omics data starting to show some good clinical utility: "Spatial immune scoring system predicts hepatocellular carcinoma recurrence" nature.com/articles/s4158… likely the tip of the molecular iceberg nature

UroToday.com (@urotoday) 's Twitter Profile Photo

Spatial transcriptomic profiling to characterize the nature of peripheral- versus transition-zone #ProstateCancer. #AuthorCommentary Parth Patel, MD and Simpa Salami Michigan Urology discuss the biological and molecular distinctions between #PCa originating in the peripheral zone vs

Spatial transcriptomic profiling to characterize the nature of peripheral- versus transition-zone #ProstateCancer. #AuthorCommentary Parth Patel, MD and <a href="/samsimsal/">Simpa Salami</a> <a href="/UMichUrology/">Michigan Urology</a> discuss the biological and molecular distinctions between #PCa originating in the peripheral zone vs
Anirban Maitra (@aiims1742) 's Twitter Profile Photo

Important publicly available resource from Tirosh Lab Weizmann Institute in Nature Cancer The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution nature.com/articles/s4301… 124 single cell datasets across 40 cancers, >2800 samples.

Luke Yun (@luke_yun1) 's Twitter Profile Photo

Yale and Google trained a 27B parameter model, C2S-Scale, to unify single-cell transcriptomics and biological language for deep reasoning across genes and cells. It outperforms prior models in interpretation, QA, and perturbation prediction using reinforcement learning

Yale and Google trained a 27B parameter model, C2S-Scale, to unify single-cell transcriptomics and biological language for deep reasoning across genes and cells. It outperforms prior models in interpretation, QA, and perturbation prediction using reinforcement learning
Michael Hofman (@drmhofman) 's Twitter Profile Photo

Stunning research from Edmond Kwan on ctDNA in theranostics: 🧬Low ctDNA predicts better response with ¹⁷⁷Lu-PSMA-617 vs. cabazitaxel chemotherapy ⚠️PTEN alterations linked to worse outcomes on cabazitaxel 🧪ATM defects tied to favorable PSMA-617 results 🩻PET quantitative

Stunning research from <a href="/EdmondMKwan/">Edmond Kwan</a> on ctDNA in theranostics:
🧬Low ctDNA predicts better response with ¹⁷⁷Lu-PSMA-617 vs. cabazitaxel chemotherapy
⚠️PTEN alterations linked to worse outcomes on cabazitaxel
🧪ATM defects tied to favorable PSMA-617 results
🩻PET quantitative
Fanying Tang (@fanyingtang) 's Twitter Profile Photo

KMT2C deficiency drives transdifferentiation of double-negative prostate cancer and confer resistance to AR-targeted therapy: Cancer Cell cell.com/cancer-cell/ab…

Fanying Tang (@fanyingtang) 's Twitter Profile Photo

External validation of a digital pathology-based multimodal artificial intelligence-derived prognostic model in patients with advanced prostate cancer starting long-term androgen deprivation therapy: biomarker study of four phase 3 controlled trials thelancet.com/journals/landi…

Fanying Tang (@fanyingtang) 's Twitter Profile Photo

High-definition spatial transcriptomic profiling of immune cell populations in colorectal cancer | Nature Genetics nature.com/articles/s4158…

Dr. Ron DePinho (@rondepinho) 's Twitter Profile Photo

Tour de force pancreas cancer study in @nature by Anirban Maitra (Anirban Maitra) MD Anderson Cancer Center, revealing profound transcriptomic heterogeneity & TME dynamics in metastases. Interesting CAF dynamics associated with cell state changes -- super cool. doi.org/10.1038/s41586…

Ming "Tommy" Tang (@tangming2005) 's Twitter Profile Photo

1/ You think clinical trial genomics is simple: compare pre‑ vs post‑treatment RNA‑seq. But even getting clean metadata? That’s a war.

1/ You think clinical trial genomics is simple: compare pre‑ vs post‑treatment RNA‑seq.
 But even getting clean metadata? That’s a war.
Myriam Chalabi (@myriamchalabi) 's Twitter Profile Photo

For an extensive overview of current and emerging #neoadjuvant #IO data across tumor types incl NSCLC, TNBC, CRC, esophagogastric + bladder cancers, melanoma and many more: So much we can learn from each other: immerse yourself! #ESMOGI25 Nature Cancer doi.org/10.1038/s43018…