AML

AML Mission Bio presentations! https://missionbio.com/resources/presentations/women-in-single-cell-elucidating-clonal-evolution-and-clonotype-immunophenotype-relationships-in-myeloid-malignancies-with-single-cell-analysis/

Single-cell mutation analysis of clonal evolution in myeloid malignancies https://www.nature.com/articles/s41586-020-2864-x?proof=t https://missionbio.com/resources/presentations/women-in-single-cell-elucidating-clonal-evolution-and-clonotype-immunophenotype-relationships-in-myeloid-malignancies-with-single-cell-analysis/

Single cell RNA sequencing of AML initiating cells reveals RNA-based evolution during disease progression https://www.nature.com/articles/s41375-021-01338-7

Fusion gene map of acute leukemia revealed by transcriptome sequencing of a consecutive cohort of 1000 cases in a single center https://www.nature.com/articles/s41408-021-00504-5

NOTCH2 and FLT3 gene mis-splicings are common events in patients with acute myeloid leukemia (AML): new potential targets in AML https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4007608

Alternative splicing redefines landscape of commonly mutated genes in acute myeloid leukemia Keywords: AML; DHX34; EZH2; alternative splicing; cancer. GSE142514 https://pubmed.ncbi.nlm.nih.gov/33876749/ PMC8054020

Single cell RNA sequencing of AML initiating cells reveals RNA-based evolution during disease progression. https://pubmed.ncbi.nlm.nih.gov/34244611/

Taming Cell-to-Cell Heterogeneity in Acute Myeloid Leukaemia With Machine Learning AML, machine learning, classification, clustering, leukaemia single-cell data could help disentangle cell heterogeneity in AML by identifying distinct core molecular signatures of leukemic cell subsets. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8117935/

Microwell-seq, 40 patients and 3 healthy donors, Patients with ribosomal protein high progenitor cells had a low remission rate. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517826/

A hypoxia risk signature for the tumor immune microenvironment evaluation and prognosis prediction in acute myeloid leukemia https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8289869/

BeatAML original paper https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280667/

CD97 expression is associated with poor overall survival in acute myeloid leukemia https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473776/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280667/

TET2 splicing model in hematopoiesis and hematopoietic diseases https://www.nature.com/articles/leu2013337

Clonal evolution https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577981/

How TARGET, BEAT AML are used https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087683/ DNA methylation in AML https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8092005/

Keywords: Acute myeloblastic leukemia; CAR-T cell; CAR-T cell immunotherapy; CD33+ leukemic stem cells; Cancer stem cells; mAB-based therapy. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106116/

"AML groups consisted of M1 (acute myeloblastic leukemia with minimal maturation), M2 (acute myeloblastic leukemia with maturation), M3 (acute promyelocytic leukemia), M4 (acute myelomonocytic leukemia), M5 (acute monocytic leukemia), and M7 (acute megakaryoblastic leukemia)."PMC5295391

feature	alias	description	reference
CD34		a stem cell marker, expressed in blast cells for AML patient	PMC5295391
CD44		hematopoiesis, associated with LSC comparing to normal HSC	PMC5295391
CLEC12A	CLL-1	Myeloid and AML blasts	PMC5295391
HAVCR2	TIM-3	~MCL1	PMC5295391
BMI1		self-renewal of HSCs	PMC5295391