How to reformat GeneSky GSA report to Plink

1924-02-28 00:00:00 +0000

Script A: transfer final report to ped (fr2ped.pl)

use strict;
use Cwd;
chdir getcwd;
open F,shift @ARGV;
my $i=1;
while(<F>){
next if !/ZS/;
my($snp,$sam,$rs,$gc,$chr,$pos,$a1,$a2,undef)=split/\s+/;
if($i eq 1){
print "$sam $sam 0 0 0 0 $a1 $a2";
}else{
print " $a1 $a2";
}
$i++;
}
print "\n";

Script B: transfer final report to ped(fr2map.pl)

use strict;
use Cwd;
chdir getcwd;
open F,shift @ARGV;
while(<F>){
next if !/ZS/;
my($snp,$sam,$rs,$gc,$chr,$pos,$a1,$a2,undef)=split/\s+/;
print "$chr $rs 0 $pos\n";
}

Step 3.0: run the script to do the job

for i in `ls *.txt | rev | cut -c 17- | rev | uniq`
do
echo $i
perl ./fr2ped.pl $i\_FinalReport.txt > $i.ped
done

for i in `ls *.txt | rev | cut -c 17- | rev | uniq`
do
echo $i
perl ./fr2map.pl $i\_FinalReport.txt > $i.map
done

step 4.0: first time to merge

rm all_my_files.txt
for i in `ls *.txt | rev | cut -c 17- | rev | uniq`
do
echo $i >> all_my_files.txt
done
grep -v ZS10 all_my_files.txt > all_files.txt

step 5.0: secome time to merge (you will receive plink-merge.missnp in the above step).remove misssnp in this step

for i in `ls *.txt | rev | cut -c 17- | rev | uniq`
do
plink --file $i --exclude IL4-merge.missnp --make-bed --out $i
done

step 6.0: merge all the binary ped and map files

plink --bfile ZS10 --merge-list allfiles.txt --make-bed --out IL4

step 7.0: extract IL4 regions

plink --bfile IL4 --pheno IL4.phen --mpheno 2 --assoc --allow-no-sex --extract IL.range --range  --adjust

How to merge 7000 VCF files with bcftools merge?

1923-02-28 00:00:00 +0000

Sometimes, maybe you want to merge >7000 vcf files/samples into one big VCF file with bcftools merge, for example PMRP have 20,000 samples/vcf files:

bcftools merge -l merge.txt -Oz -o merge.vcf.gz

if the sample counts <1021, everything is okay. However, if it is >= 1021, bcftools merge will reports:

[E::hts_idx_load3] Could not load local index file '229209.fstl1.vcf.gz.tbi'
Failed to open 229209.fstl1.vcf.gz: could not load index

Okay. Here is my final solution developed based on WouterDeCoste’s post. I hope it is helpful. One of my friends told me his computer allowed merging 7000 VCF at one time. I am not sure whether it is caused by a specific file operating setting.

ls *.vcf.gz | split -l 500 - subset_vcfs

for i in subset_vcfs*; 
do 
bcftools merge -0 -l $i -Oz -o merge.$i.vcf.gz; 
tabix -p vcf merge.$i.vcf.gz
done

ls merge.*.vcf.gz > merge.txt
bcftools merge -l merge.txt -0 -Oz -o all_merged.vcf.gz
bcftools annotate -x INFO,^FORMAT/GT all_merged.vcf.gz -Oz -o Final.vcf.gz

-0 is to set missing to reference

Another example I want to share as the following: Project Exome-sequencing:

1, rename WP files to -a files

use strict;
my @file=glob("WP_*.gz");
foreach my $file(@file){
my(undef,$id,undef)=split/_/,$file;
print "$file\t$id\n";
system("cp $file $id-a.filtered.vcf.gz")
}

2, the file name is not exactly same with sample id for the vcf. What’s more, vcfs are from to project

rm sample.txt
for i in `ls *.vcf.gz`
do
echo $i
#bcftools index -f -t $i
bcftools query -l $i >> sample.txt
done

3, sampleid is too long, rename the sample id

use strict;
use Cwd;
chdir getcwd;
my $file="sample.txt";
open F, $file || die "cannot open $file\n";
while(<F>){
chomp;
my $file=$_;
my($id,undef)=split/.filtered.vcf.gz/,$file;
if($id =~/-a/){
my ($name,undef)=split/-/,$id;
print "$id $name\n";
}else{
my (undef,$name,undef)=split/_/,$id;
print "$id $name\n";
}
}

4, sometimes, the computer have limited ulimit setting, you cannot merge too many samples at the same time. Here, I showed the solution to merge every 200 files and finally we will merge 7000 samples.

ls *.vcf.gz | split -l 200 - subset_vcfs
for i in subset_vcfs*; 
do 
echo $i
bcftools merge -0 -l $i -Oz -o merge.$i.vcf.gz 
tabix -p vcf merge.$i.vcf.gz
done
ls merge.*.vcf.gz > merge.txt
bcftools merge -l merge.txt -0 -Oz -o all_merged.vcf.gz
bcftools annotate -x INFO,^FORMAT/GT all_merged.vcf.gz -Oz -o Final.vcf.gz

Automatic GWAS and Post-GWAS Analysis Pipeline

1922-02-28 00:00:00 +0000

Here, I summarized Automatic GWAS and Post-GWAS Analysis Pipeline Published Works:

How to install ANNOVAR in DeepThought@UW-Madison

1921-02-28 00:00:00 +0000

1, download ANNOVAR: http://annovar.openbioinformatics.org/en/latest/user-guide/download/

cd ~/tools/annovar
annotate_variation.pl -buildver hg19 -downdb cytoBand humandb/
annotate_variation.pl -buildver hg19 -downdb -webfrom annovar refGene humandb/

# just for allele frequency
# annotate_variation.pl -downdb -webfrom annovar exac03 humandb -buildver hg38  &
# annotate_variation.pl -downdb -webfrom annovar esp6500siv2 humandb -buildver hg38 &
annotate_variation.pl -downdb -webfrom annovar esp6500siv2_all humandb -buildver hg38 &
annotate_variation.pl -downdb -webfrom annovar gnomad_exome humandb -buildver hg38 &

# whole-exome data
annotate_variation.pl -downdb -webfrom annovar 1000g2015aug humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar kaviar_20150923 humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar hrcr1 humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar cg69 humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar gnomad_genome humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar dbnsfp30a humandb -buildver hg38 &
annotate_variation.pl -downdb -webfrom annovar esp6500siv2 humandb -buildver hg38 &
annotate_variation.pl -downdb esp6500siv2 humandb -buildver hg38 &

# whole-genome data
annotate_variation.pl -downdb -webfrom annovar gerp++ humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar cadd humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar cadd13 humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar fathmm humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar eigen humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar gwava humandb -buildver hg38  &

# CNV
annotate_variation.pl -downdb -webfrom annovar dbscsnv11 humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar spidex humandb -buildver hg38  &

# disease-specific variants
annotate_variation.pl -downdb -webfrom annovar clinvar_20160302 humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar cosmic70 humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar icgc21 humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar nci60 humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar dbnsfp35c humandb -buildver hg38  &
annotate_variation.pl -downdb -webfrom annovar dbnsfp33a humandb -buildver hg19  &
annotate_variation.pl -downdb -webfrom annovar dbnsfp35a humandb -buildver hg19  &
annotate_variation.pl -downdb -webfrom annovar dann humandb --buildver hg38 &
annotate_variation.pl -downdb -webfrom annovar dann humandb --buildver hg19 &
annotate_variation.pl -downdb -webfrom annovar ljb23_all humandb --buildver hg19&

# GWAS
annotate_variation.pl -buildver hg38 -downdb -webfrom annovar gwasCatalog humandb/ &
annotate_variation.pl -buildver hg38 -downdb  tfbsConsSites humandb/ 
annotate_variation.pl -buildver hg38 -downdb -webfrom annovar wgRna humandb/ &
annotate_variation.pl -buildver hg38 -downdb targetScanS humandb/ 
annotate_variation.pl -downdb -webfrom annovar dann humandb --buildver hg38 &
annotate_variation.pl -buildver hg38 -downdb  tfbsConsSites humandb/ 
annotate_variation.pl -buildver hg38 -downdb  tfbsConsSites humandb/ 
annotate_variation.pl -buildver hg38 -downdb -webfrom annovar gnomad_genome humandb/ 
annotate_variation.pl -buildver hg38 -downdb -webfrom ucsc gnomad_genome humandb/ 

2, ANNOVAR now takes VCF as standard input

bcftools view -G Final.vcf.gz --threads 32 -Ov -o avinput.vcf
table_annovar.pl -vcfinput avinput.vcf ~/tools/annovar/humandb/ --thread 12 -buildver hg19 -out myanno -remove -protocol refGene,dbnsfp33a -operation gx,f -nastring . -otherinfo -polish -xref ~/tools/annovar/humandb/gene_fullxref.txt

3, SNP distribution patterns, how many intergenic? how many exomic?

bcftools view -G Final.vcf.gz --threads 32 -Ov -o avinput.vcf
table_annovar.pl -vcfinput avinput.vcf ~/tools/annovar/humandb/ --thread 12 -buildver hg19 -out myanno -remove -protocol refGene,dbnsfp33a -operation gx,f -nastring . -otherinfo -polish -xref ~/tools/annovar/humandb/gene_fullxref.txt

data<-read.table("c1",as.is=T)
anno<-data[,1]
anno[anno=="ncRNA_UTR5"]<-"ncRNA_exonic"
anno[anno=="ncRNA_exonic;splicing"]<-"ncRNA_exonic"
anno[anno=="exonic;splicing"]<-"splicing"
anno[anno=="UTR5;UTR3"]<-"exonic"
anno[anno=="ncRNA_splicing"]<-"splicing"
anno[anno=="upstream;downstream"]<-"intergenic"
input<-table(anno)
pdf("pie.annovar.pdf")
pie(input,col=rainbow(length(input)),main="N=13,494,289 SNPs")
dev.off()

4, Distance distribution to exome regions?

perl -lane '{print $1 if /dist=(\d+)/}' myanno.refGene.variant_function > dist

data<-read.table("dist",as.is=T)
distance<-data[,1]

pdf("dist.annovar.pdf")
hist(distance,col=rainbow(20),main=paste("N=",length(distance),"SNPs",sep=" "))
dev.off()

distance<-distance[distance<100000]
pdf("dist.100k.annovar.pdf")
hist(distance,col=rainbow(20),main=paste("N=",length(distance),"SNPs",sep=" "),xlab="distance to nearby exome (bp)")
dev.off()

distance<-distance[distance<10000]
pdf("dist.10k.annovar.pdf")
hist(distance,col=rainbow(20),main=paste("N=",length(distance),"SNPs",sep=" "),xlab="distance to nearby exome (bp)")
dev.off()

distance<-distance[distance<1000]
pdf("dist.1k.annovar.pdf")
hist(distance,col=rainbow(20),main=paste("N=",length(distance),"SNPs",sep=" "),xlab="distance to nearby exome (bp)")
dev.off()

5, PCA analysis

awk '{print $4}' hsa.gff3.hg19.bed  | sort -u > hsa.gff3.hg19.snp
plink --bfile /gpfs/home/guosa/hpc/db/hg19/1000Genome/plink/G1000plink --extract hsa.gff3.hg19.snp --make-bed --out G1000.miRNA
plink --bfile ROI.RA3000.dbsnp --bmerge G1000.miRNA --allow-no-sex --make-bed --out ./PCA/ROI
plink --bfile ROI --threads 31 --cluster --mds-plot 2
plink --bfile ROI --threads 31 --pca 2 'header' --out ROI

hapmap2<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/AnnotationDatabase/master/hapmap2.pop",head=F)
hapmap3<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/AnnotationDatabase/master/hapmap3.pop",head=T)
G1000Sam <-read.table("https://raw.githubusercontent.com/Shicheng-Guo/AnnotationDatabase/master/1000G/1000GenomeSampleInfo.txt",head=F,as.is=T)
G1000Super<-read.table("https://raw.githubusercontent.com/Shicheng-Guo/AnnotationDatabase/master/1000G/superpopulation.txt",head=F,sep="\t")
G1000Sam$superpop<-G1000Super[match(G1000Sam$V3,G1000Super$V1),]$V2
write.table(G1000Sam,file="1000GenomeSampleInfo.txt",quote=F,sep="\t",col.names=F,row.names=F)

eigenvec<-read.table("plink.eigenvec",head=T)
head(eigenvec)
pop<-as.character(G1000Sam[match(eigenvec[,2],G1000Sam[,2]),3])
super<-as.character(G1000Sam[match(eigenvec[,2],G1000Sam[,2]),5])
pop[is.na(pop)]<-"GHRA"
super[is.na(super)]<-"GHRA"
eigenvec$pop=pop
eigenvec$super=super
eigenvec$col=as.numeric(as.factor(super))
eigenvec$pch=as.numeric(as.factor(super))

set<-unique(data.frame(pch=eigenvec$pch,col=eigenvec$col,legend=eigenvec$super))

for(i in 1:15){
jpeg(paste("pca.super",i,".jpg",sep=""))
plot(eigenvec[,3],eigenvec[,4],pch=16,col=eigenvec$col+i,xlab="principle component 1",ylab="principle componment 2",cex.axis=1.5,cex.lab=1.5,cex=1)
legend("topright",pch=16,legend=set$legend,col=set$col+i,bty="n",cex=1)
dev.off()
}

How to Prepare Annotation DB Folder for Bioinformatics Analysis

1920-02-28 00:00:00 +0000

Here, I list all the used annotation in my previous publication:

Step by step to prepare your db folder (hg38):

wget http://hgdownload.cse.ucsc.edu/goldenpath/hg38/database/cytoBand.txt.gz -O cytoBand.hg38.bed.gz
wget http://hgdownload.cse.ucsc.edu/goldenpath/hg38/database/cpgIslandExt.txt.gz -O cpgIsland.hg38.bed.gz
wget https://raw.githubusercontent.com/Shicheng-Guo/miRNA-RA/master/db/hsa.gff.hg19.bed -O hsa.gff3.hg38.bed 
wget http://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/liftOver -O liftOver
wget http://hgdownload.soe.ucsc.edu/goldenPath/hg18/liftOver/hg18ToHg19.over.chain.gz -O hg18ToHg19.over.chain.gz
wget http://hgdownload.soe.ucsc.edu/goldenPath/hg19/liftOver/hg19ToHg38.over.chain.gz -O hg19ToHg38.over.chain.gz
wget http://hgdownload.soe.ucsc.edu/goldenPath/hg38/liftOver/hg38ToHg19.over.chain.gz -O hg38ToHg19.over.chain.gz
wget https://raw.githubusercontent.com/Shicheng-Guo/GscRbasement/master/manhattan.qqplot.R -O manhattan.plot.R
wget https://raw.githubusercontent.com/Shicheng-Guo/Gscutility/master/localhit.pl -O localhit.pl
wget https://raw.githubusercontent.com/Shicheng-Guo/rheumatoidarthritis/master/R/make.fancy.locus.plot.unix.R -O make.fancy.locus.plot.unix.R

How to Prepare China and USA Map with R

1919-02-28 00:00:00 +0000

Plan-A

setwd("C:\\Users\\Schrodi Lab\\Documents\\GitHub\\rheumatoidarthritis\\RA\\ASA\\MIR\\manuscript\\map")
install.packages("maptools")
install.packages("rgdal")
install.packages("maps")
install.packages("usmap")
install.packages("data.table")
install.packages("ggsn")
install.packages("ggrepel")
install.packages("rmarkdown")
library(ggplot2)
library(maps)
library(usmap)
library(data.table)
library(ggsn) 
library(ggrepel) 
library("maptools")
library("rgdal")
library("rmarkdown")
china_map <- rgdal::readOGR("bou2_4p.shp")
china_province = setDT(china_map@data)
setnames(china_province, "NAME", "province")
china_province[, province:=iconv(province, from = "GBK", to = "UTF-8")] 
china_province[, id:= .I-1] 
china_province[, table(province)]
china_province[, province:= as.factor(province)]
dt_china = setDT(fortify(china_map))
dt_china[, id:= as.numeric(id)]
setkey(china_province, id); setkey(dt_china, id)
dt_china <- china_province[dt_china]
province_CH <- china_province[, levels(province)] # the CH are in UTF-8 code
province_EN <- c("Shanghai", "Yunnan", "Inner Mongolia", "Beijing", "Taiwan",
                 "Jilin", "Sichuan", "Tianjin City", "Ningxia", "Anhui",
                 "Shandong", "Shanxi", "Guangdong", "Guangxi ", "Xinjiang",
                 "Jiangsu", "Jiangxi", "Hebei", "Henan", "Zhejiang",
                 "Hainan", "Hubei", "Hunan", "Gansu", "Fujian",
                 "Tibet", "Guizhou", "Liaoning", "Chongqing", "Shaanxi",
                 "Qinghai", "Hong Kong", "Heilongjiang"
)
value <- c(8893483, 12695396,  8470472,  7355291, 23193638,  9162183, 26383458,  3963604,  1945064, 19322432, 30794664, 10654162, 32222752, 13467663,  6902850, 25635291, 11847841, 20813492, 26404973, 20060115, 2451819, 17253385, 19029894,  7113833, 11971873,   689521, 10745630, 15334912, 10272559, 11084516, 1586635,  7026400, 13192935)
input_data <- data.table(province_CH, province_EN, value)
setkey(input_data, province_CH)
setkey(dt_china, province)
china_map_pop <- input_data[dt_china[AREA>0.1,]]
label_dt <- china_map_pop[, .(x = mean(range(long)), y = mean(range(lat)), province_EN, province_CH), by = id]
label_dt <- unique(label_dt)
setkey(label_dt, province_EN)
# I have fine-tuned the label position of some provinces
label_dt['Inner Mongolia', `:=` (x = 110, y = 42)]
label_dt['Gansu', `:=` (x = 96.3, y = 40)]
label_dt['Hebei', `:=` (x = 115.5, y = 38.5)]
label_dt['Liaoning', `:=` (x = 123, y = 41.5)]
rmarkdown::paged_table(china_map_pop[!is.na(province_CH),])

ggplot(china_map_pop, aes(x = long, y = lat, group = group, fill="blank")) +
  labs(fill = "Population (outdated)")+
  geom_polygon()+
  geom_path()+
  blank() 

  scale_fill_gradientn(colours=rev(heat.colors(10)),na.value="grey90",
  guide = guide_colourbar(barwidth = 0.8, barheight = 10)) + 
  + 
  geom_text(data = label_dt, aes(x=x, y=y, label = ""),inherit.aes = F) +
  scalebar(data = china_map_pop, dist = 500, dist_unit = "km",
  transform = T, model = "WGS84",
  border.size = 0.4, st.size = 2
  ) 

Plan-B

install.packages("maptools")
install.packages("rgdal")
install.packages("maps")
install.packages("usmap")
install.packages("data.table")
install.packages("ggsn")
install.packages("ggrepel")
install.packages("rmarkdown")
install.packages("mapdata")

library(ggplot2)
library(maps)
library(usmap)
library(data.table)
library(ggsn) 
library(ggrepel) 
library("maptools")
library("rgdal")
library("rmarkdown")
library(mapdata)
library(maptools)

map("china", col = "gray40", ylim = c(18,54))
china_map <- readShapePoly("bou2_4p.shp")
Shanghai = china_map[china_map$ADCODE99 == 310000,]
plot(Shanghai)

mydat = readShapePoly("bou2_4p.shp")
Shanghai = mydat[substr(as.character(mydat$ADCODE99), 1, 2) == '31',]
mysh = fortify(Shanghai, region = 'NAME99')

head(fortify(Shanghai))

mysh = transform(mysh, id = iconv(id, from = 'GBK'), group = iconv(group, from = 'GBK'))
head(mysh)


Shanghai = mydat[substr(as.character(mydat$ADCODE99), 1, 2) == '31',]
mysh = fortify(Shanghai, region = 'NAME99')
mysh = transform(mysh, id = iconv(id, from = 'GBK'), group = iconv(group, from = 'GBK'))
head(mysh)


install.packages("mapproj")
library(maptools)
library(ggplot2)
library(mapproj)
mydat = readShapePoly("bou2_4p.shp")
mymap<-ggplot(data = fortify(mydat)) +
  geom_polygon(aes(x = long, y = lat, group = id), colour = "black",
  fill = NA) +
  blank()
print(mymap + coord_map())
Shanghai = mydat[mydat$ADCODE99 == 310000,]
plot(Shanghai)
mysh=fortify(Shanghai)
mysh$id=1:nrow(mysh)
head(mysh)

sample = data.frame(id = unique(sort(mysh$id)))
sample$num = runif(length(mysh$id))
sample

csmap = ggplot(sample) +
  geom_map(aes(map_id = id, fill = num), color = "white", map = mysh) +
  scale_fill_gradient(high = "darkgreen",low = "lightgreen") +
  expand_limits(mysh) + coord_map() + blank()
print(csmap)

head(mysh)

FDA and drug development pipeline

1918-02-28 00:00:00 +0000

  • J&J defends Darzalex with FDA approval for faster dosing
  • Rcpi: R/Bioconductor Package as an Integrated Informatics Platform for Drug Discovery: https://www.bioconductor.org/packages/release/bioc/vignettes/Rcpi/inst/doc/Rcpi.html
  • TAGRISSO: Targeted therapies to cancer that has tested positive for certain types of EGFR mutations. TAGRISSO specifically targets and blocks mutated EGFR found on cancer cells.
  • Fragment-based lead discovery (FBLD) also known as fragment-based drug discovery (FBDD)
  • BRAF is a human gene that encodes a protein called B-Raf. The gene is also referred to as proto-oncogene
  • The Drug Development Process: The Drug Development Process
  • In order to incentivize the development of new drugs, the FDA grants drug developers market exclusivity for a period of five years after a new drug is approved, during which time, no other firm is permitted to sell the drug, whether or not it is protected by a patent.
  • China National PGx Data Science Consortium (CNPGx)
  • KEGG DRUG: Methotrexate https://www.genome.jp/dbget-bin/www_bget?dr:D00142

How to Install Ensembl Variant Effect Predictor

1917-02-28 00:00:00 +0000

  • CRAN Task View: Meta-Analysis: https://cran.rstudio.com/web/views/MetaAnalysis.html

perl -MCPAN -Mlocal::lib -e 'CPAN::install(Archive::Zip)'
perl -MCPAN -Mlocal::lib -e 'CPAN::install(DBI)'
perl -MCPAN -Mlocal::lib -e 'CPAN::install(Try::Tiny)'

git clone https://github.com/Ensembl/ensembl-vep.git
cd ensembl-vep
perl INSTALL.pl
  • regression line vs regression plane
  • response ~ multiple variables (linear parameters) + error (~N(0,))
  • Goodness of fit
  • Add extra features always make better fitting.
  • Adjust R2 (adjusted with the numbers of predictors)
  • AIC, BIC, Mallow’s Cp
  • Variance inflation factor (VIF) VIF>9, multicollinearity

FDA approved drugs and the mechanism

1916-02-28 00:00:00 +0000

  • 2013: Bluebird Bio: autologous CD34+ hematopoietic stem cells transduced with LentiGlobin BB305 lentiviral vector encoding the human BA-T87Q-globin gene

  • The FDA has approved the first drug to treat the rapid-aging disease progeria.The drug is a “testament to the power of basic research,” says Tom Misteli, a cell biologist at the National Cancer Institute in Bethesda, Md, who was not involved with work on the drug. Zokinvy builds on decades of research on many aspects of the lamin A protein, including the “seemingly esoteric chemical modification” that forms progerin, he says.

  • Setmelanotide is an investigational, melanocortin-4 receptor (MC4R) agonist. The MC4R is part of the key biological pathway that independently regulates energy expenditure and appetite. Variants in genes may impair the function of the MC4R pathway, potentially leading to insatiable hunger and early-onset, severe obesity. Rhythm is currently developing setmelanotide as a targeted therapy to restore the function of an impaired MC4R pathway and, in so doing, reduce hunger and weight in patients with rare genetic disorders of obesity. Currently, no pharmacologic therapies exist to treat these conditions. The FDA has granted Breakthrough Therapy designation to setmelanotide for the treatment of obesity associated with genetic defects upstream of the MC4R in the central melanocortin pathway, which includes pro-opiomelanocortin (POMC) deficiency obesity and leptin receptor (LEPR) deficiency obesity. The European Medicines Agency (EMA) has also granted PRIority MEdicines (PRIME) designation for setmelanotide for the treatment of obesity and the control of hunger associated with deficiency disorders of the MC4R pathway. Both the FDA and EMA have granted orphan drug status to setmelanotide for POMC and LEPR deficiency obesities. The FDA has accepted Rhythm’s New Drug Application (NDA) for setmelanotide for the treatment of POMC and LEPR deficiency obesities, granted Priority Review of the NDA and assigned a Prescription Drug User Fee Act (PDUFA) goal date of November 27, 2020. Rhythm expects to complete submission of a Marketing Authorization Application (MAA) for setmelanotide to treat individuals living with POMC deficiency obesity or LEPR deficiency obesity to the EMA in the second quarter of 2020.

  • RYTM Rhythm Pharmaceuticals, Inc. PDUFA, When, Friday, Nov 27, 2020, Description, 2020-11-27 The FDA has accepted Rhythms New Drug Application (NDA) for setmelanotide for the treatment of POMC and LEPR deficiency obesities, granted Priority Review of the NDA and assigned a Prescription Drug User Fee Act (PDUFA) goal date of November 27, 2020. https://www.globenewswire.com/news-release/2020/06/24/2052662/0/en/Rhythm-Pharmaceuticals-Announces-Positive-Results-from-Phase-2-Study-of-Once-weekly-Formulation-of-Setmelanotide-in-Healthy-Obese-Volunteers.html

  • Johnson & Johnson (J&J) is an American multinational healthcare company focused on the development and commercialization of pharmaceutical, medical device, and consumer packaged products. The pharmaceutical portfolio offers products for Cardiovascular, Endocrinology, Immunology, Neuroscience, and Oncology. J&J has 14 drugs in its oncology portfolio with 6 approved products including Darzalex, Imbruvica, Velcade, Zytiga, Balversa, and Niraparib. Imbruvica, an approved small molecule drug used to treat B cell cancers like mantle cell lymphoma, chronic lymphocytic leukemia, and Waldenstrom’s macroglobulinemia and jointly marketed by Janssen Biotech and Pharmacyclics (AbbVie) has generated the revenue $3.41B in 2019. In Apr’19, FDA approved Johnson & Johnson’s Balversa (erdafitinib) for advanced or metastatic urothelial carcinoma.

  • 11/24/2020: FDA Approves Oxlumo (lumasiran) for the Treatment of Primary Hyperoxaluria Type 1.

  • Repurposing Drugs in Oncology (ReDO)—chloroquine and hydroxychloroquine as anti-cancer agents

  • 11/05/2020, Controversial news: FDA scientists appear to offer major endorsement of Biogen’s controversial Alzheimer’s treatment. In a lengthy document released Wednesday, FDA staff appeared to endorse approving the treatment, which would become the first new Alzheimer’s therapy in nearly two decades. The commentary, which provides the first glimpse at how FDA scientists view the oft-debated treatment, comes ahead of a Friday meeting of outside advisers, who will issue a nonbinding vote on whether to recommend aducanumab’s approval.

  • Protein methyltransferases (PMTs) are a large group of enzymes that use a common mechanism to catalyse the methylation of their substrates. PMTs bind the cofactor S-adenosyl-L-methionine (SAM) and the substrate protein to form a ternary complex. Direct transfer of the methyl group from SAM to an amino acid side chain of the substrate then occurs. Protein methylation of histones is used as an epigenetic mechanism to regulate transcription and gene stability, and recently it has also been shown to be a means by which the activity of other proteins – including enzymes such as certain kinases – may be regulated. Dysregulation of the activity of some PMTs has been shown to play an oncogenic role in a number of human cancers. Several PMT inhibitors have now entered clinical trials and Tazemetostat, an EZH2 inhibitor, gained accelerated approval from the FDA in January 2020 for the treatment of metastatic or locally advanced epithelioid sarcoma.

  • A side effect is usually regarded as an undesirable secondary effect which occurs in addition to the desired therapeutic effect of a drug or medication. Side effects may vary for each individual depending on the person’s disease state, age, weight, gender, ethnicity and general health. Side effects can occur when commencing, decreasing/increasing dosages, or ending a drug or medication regimen. Side effects may also lead to non-compliance with prescribed treatment. When side effects of a drug or medication are severe, the dosage may be adjusted or a second medication may be prescribed. Lifestyle or dietary changes may also help to minimize side effects.

  • 10/30/2020: FDA Approves Eysuvis (loteprednol etabonate) Ophthalmic Suspension for the Short-Term Treatment of the Signs and Symptoms of Dry Eye Disease. Corticosteroids like loteprednol etabonate inhibit the inflammatory response to a variety of inciting agents and likely delay or slow healing Label. They inhibit the edema, fibrin deposition, capillary dilation, leukocyte migration, capillary proliferation, fibroblast proliferation, deposition of collagen, and scar formation that are commonly associated with inflammation Label. While glucocorticoids are known to bind to and activate the glucocorticoid receptor, the molecular mechanisms involved in glucocorticoid/glucocorticoid receptor-dependent modulation of inflammation are not clearly established Label. Moreover, corticosteroids are thought to inhibit prostaglandin production through several independent mechanisms Label. In particular, corticosteroids are thought to act by the induction of phospholipase A2 inhibitory proteins, collectively called lipocortins. It is postulated that these proteins control the biosynthesis of potent mediators of inflammation such as prostaglandins and leukotrienes by inhibiting the release of their common precursor arachidonic acid. Arachidonic acid is released from membrane phospholipids by phospholipase A2.

  • 10/30/2020: the gnomAD Production Team is proud to announce the release of gnomAD v3.1, an update to our previous genome release. The v3.1 data set adds 4,454 genomes, bringing the total to 76,156 whole genomes mapped to the GRCh38 reference sequence. (Our most recent exome release is available in gnomAD v2.1.)

  • SAN DIEGO, Oct. 25, 2020 /PRNewswire/ – Mirati Therapeutics, Inc. (NASDAQ: MRTX), a clinical-stage targeted oncology company, today announced preliminary results from the Company’s mutant KRAS selective inhibitor programs. The preliminary results included updated clinical data of adagrasib (MRTX849), the Company’s KRAS G12C inhibitor, presented at the 32nd EORTC-NCI-AACR Symposium on Molecular Targets and Therapeutics (“ENA”) and initial preclinical in vivo data of MRTX1133, the Company’s selective and potent potential first-in-class KRAS G12D inhibitor.

  • From the evening of Sunday, June 9, to the morning of Friday, June 21, 2019, the Russell Sage Foundation (RSF) sponsored the 3rd Summer Institute in Social-Science Genomics, held at the Pepper Tree Inn in Santa Barbara, California. We have the 2019 videos here: https://www.rsfgenomicsschool.com/2019-materials. The 2017 ones aren’t on the website, but i found them on youtube here: https://www.youtube.com/channel/UCpwuOWUVasa168eWFhX-48A/videos

  • modern technique has many different approaches to looking for drug targets: phenotypic screening, gene association studies, chemo proteomics, transgenetic organisms, imaging, biomarkers and many other methods

  • Early stages of drug discovery start with initial steps of target identification and moves to the later stages of lead optimization. Multiple sources including academic research, clinical works and commercial sector help in the identification of a suitable disease target. The chosen target is then used by the pharmaceutical industry and more recently by some academic centers to identify molecules for making acceptable drugs. The process involves various early steps

  • FDA Approves Veklury (remdesivir) for the Treatment of COVID-19

  • Lead discovery is the beginning of the search for specific molecules that may bind the drug target. It is a key stage for drug development. The search normally starts with a collection of molecules in the drug company. This collection is called a library. The library is screened with a binding assay to find promising molecules with good binding. These are called hits. Hits are then screened for their potential ADME properties and even activity in animals. The best hits will be advanced as lead molecules for further investigation.

  • The goal of lead optimization in drug development is to design a molecule that satisfies the safety criteria for an IND submission with sufficient promise for efficacy. Lead optimization begins with a molecule that was identified during lead discovery. The original lead will have good properties (potency, ADME, Absorption, Distribution, Metabolism, and Excretion) that need to be improved for the molecule to enter clinical trials. Lead optimization involves a series of structural changes that allow the optimization team to understand the structure-activity relationships of the lead. The goal of lead optimization is not to design the signle best molecule, but to design a lead that satisfies the safety criteria for an IND submission with sufficient promise for efficacy

  • Optimization of the ADME (Absorption, Distribution, Metabolism, and Excretion) properties of the drug molecule is often the most difficult and challenging part of the whole drug discovery process. The ADME profile will also have a major impact on the likelihood of success of a drug

  • 10/14/2020: FDA Approves Inmazeb (atoltivimab, maftivimab and odesivimab-ebgn) Antibody Cocktail for Ebola (Zaire Ebolavirus)
  • Oxycodone is a semisynthetic opioid analgesic derived from thebaine in Germany in 1917. It is currently indicated as an immediate release product for moderate to severe pain and as an extended release product for chronic moderate to severe pain requiring continuous opioid analgesics for an extended period.Label The first oxycodone containing product, Percodan, was approved by the FDA on April 12, 1950
  • 2020: IL-17A Antagonist to Receive U.S. FDA Approval for the Treatment of Non-Radiographic Axial Spondyloarthritis (nr-axSpA).
  • Roche announces FDA approval of Gavreto (pralsetinib) for the treatment of adults with metastatic RET fusion-positive non-small cell lung cancer
  • Brolucizumab (Beovu®) is an FDA approved vascular endothelial growth factor (VEGF) inhibitor for the treatment of neovascular age related macular degeneration #AMD. Brolucizumab targets the major VEGF-A isoforms: VEGF110, VEGF121, and VEGF165. Inhibition of these VEGF-A isoforms reduce proliferation of endothelial cells, vascularization of the tissue, and permeability of the #vasculature. Brolucizumab is the first FDA approved anti-VEGF to offer both greater fluid resolution versus aflibercept and the ability to maintain eligible wet #AMD patients on a three-month dosing interval immediately after a three-month loading phase with uncompromised efficacy. #Brolucizumab successfully completed phase III development in wet age-related macular degeneration (AMD) meeting the primary efficacy endpoint of non-inferiority to aflibercept in mean change in best corrected visual acuity, #BCVA from baseline to week 48. Furthermore, brolucizumab demonstrated superiority to aflibercept in key secondary endpoint measures of disease #activity in wet AMD, a leading cause of blindness in two head-to-head pivotal Phase III studies.

  • Golodirsen (Vyondys 53®) is an FDA approved morpholino antisense oligomer designed to treat Duchenne Muscular Dystrophy (DMD) which is an X-linked condition leading to progressive muscle degeneration that begins in early childhood. Golodirsen is a form of antisense therapy which works by inducing exon skipping in the dystrophin gene and thereby increasing the amount of dystrophin protein available to muscle fibers. The hallmark of DMD is the absence of the important muscle stabilizing protein, dystrophin, that is caused by a deletion mutation on the DMD (dystrophin) gene. This results in the production of a non-functional protein. Lack of dystrophin protein leads to progressive muscle weakness and degeneration. Golodirsen binds to exon 53 of dystrophin pre-mRNA on the DMD gene, excluding this protein coding unit during mRNA processing. The exclusion (or skipping) changes out-of-frame mRNA to in-frame mRNA. A similar drug used in the treatment of other types of DMD is eteplirsen, which targets a different genetic mutation. Eteplirsen is a phosphoramidite morpholino sequence complementary to a portion of exon 51 and then force the exclusion of exon 51 from the mature DMD mRNA.

  • Bruton’s tyrosine kinase (abbreviated Btk or BTK), also known as tyrosine-protein kinase BTK, is a tyrosine kinase that is encoded by the BTK gene in humans. BTK plays a crucial role in B cell development. #Ibrutinib (Imbruvica®), a selective Bruton’s tyrosine kinase inhibitor. #Poseltinib is an inhibitor of Bruton’s tyrosine kinase (BTK) with potential anti-inflammatory activity. #Acalabrutinib for relapsed mantle cell lymphoma and #Zanubrutinib for mantle cell lymphoma. Compared to the first-generation BTK inhibitor #ibrutinib, #zanubrutinib (Brukinsa®) displays higher potency and selectivity for BTK with fewer off-target effects. Upon administration, #poseltinib inhibits the activity of BTK and prevents the activation of the B-cell antigen receptor (BCR) signaling pathway. This prevents the activation of BTK-mediated inflammatory pathways. #Poseltinib is under investigation for the treatment of rheumatoid arthritis, lupus, lupus nephritis, Sjögren’s syndrome, and other immunological conditions. #Evobrutinib is an oral, highly selective inhibitor of Bruton’s tyrosine kinase (BTK) which is important in the development and functioning of various immune cells including B lymphocytes and macrophages with potential antineoplastic activity.

  • FDA approved Fintepla (fenfluramine), a Schedule IV controlled substance, for the treatment of seizures associated with Dravet syndrome in patients age 2 and older. Dravet syndrome is a life-threatening, rare and chronic form of epilepsy. It is often characterized by severe and unrelenting seizures despite medical treatment. Fintepla labeling includes a boxed warning stating the drug is associated with valvular heart disease (VHD) and pulmonary arterial hypertension (PAH). Because of these risks, patients must have cardiac monitoring using echocardiograms performed before treatment, every six months during treatment, and once three to six months after treatment is discontinued. If the echocardiogram shows signs of VHD, PAH, or other cardiac abnormalities, health care professionals must consider the benefits and risks of continuing treatment with Fintepla for the patient. Because of the risks of VHD and PAH, Fintepla is available only through a restricted drug distribution program, under a risk evaluation and mitigation strategy (REMS). The Fintepla REMS requires health care professionals who prescribe Fintepla and pharmacies that dispense Fintepla to be specially certified in the Fintepla REMS and that patients be enrolled in the REMS. As part of the REMS requirements, prescribers and patients must adhere to the required cardiac monitoring with echocardiograms to receive Fintepla. The most common adverse reactions in clinical studies were decreased appetite; drowsiness, sedation and lethargy; diarrhea; constipation; abnormal echocardiogram; fatigue or lack of energy; ataxia (lack of coordination), balance disorder, gait disturbance (trouble with walking); increased blood pressure; drooling, salivary hypersecretion (saliva overproduction); pyrexia (fever); upper respiratory tract infection; vomiting; decreased weight; risk of falls; and status epilepticus.

  • A new world of RNA-binding proteins! Science Advances reports RNA binding protein #PCBP1 (Poly-RC-Binding Protein 1) is an intracellular immune checkpoint for shaping T cell responses in cancer immunity. The authors identified #PCBP1 as an intracellular immune checkpoint that is up-regulated in activated T cells to prevent conversion of effector T cells into regulatory T cells, by restricting the expression of Teff cell –intrinsic Treg commitment programs. T cell–specific deletion of Pcbp1 favored Teff transvert to Treg, enrolled multiple inhibitory immune checkpoint molecules including PD-1, TIGIT, and VISTA on tumor-infiltrating lymphocytes, and decrease antitumor immunity. And just few days ago, in a Nature paper RNA-binding protein #PTBP1 (Polypyrimidine Tract Binding Protein 1) knock-down could convert #astrocytes to new neurons that innervate into and repopulate endogenous neural circuits. RNA-binding protein are not just binding…

  • Synthetic lethality has been successfully applied in cancer drug development. #BRCA and #PARP is an classic example. Cancer cells with both BRCA1/2 and PARP loss-of-function will induce the apoptosis and cell death. Olaparib is a #PARP inhibitor, inhibiting poly ADP ribose polymerase #PARPP), an enzyme involved in DNA repair. It acts against cancers in people with hereditary #BRCA1 or #BRCA2 mutations, which include some ovarian, breast, and prostate cancers. Recently, FDA approved Olaparib plus Bevacizumab as maintenance treatment for ovarian cancer. Bevacizumab is a recombinant humanized monoclonal antibody that blocks #angiogenesis by inhibiting vascular endothelial growth factor A #VEGFA which is a growth factor protein that stimulates #angiogenesis in a variety of diseases. #VEGFA is upregulated in many tumors and its expression is correlated with tumor development and is a target in many developing cancer therapeutics.

  • DNA driver mutation mediated drug-target is a fantastic strategy to accelerate anti-cancer drug development. Capmatinib is a MET inhibitor being evaluated as a treatment for first-line and previously treated patients with locally advanced or metastatic MET exon 14 skipping (METex14) mutated non-small cell lung cancer (NSCLC). METex14 mutations occur in 3-4% of newly diagnosed advanced NSCLC cases and is a recognized oncogenic driver. MET exon 14 alterations result in increased MET protein levels due to disrupted ubiquitin-mediated degradation. MET belongs to receptor tyrosine kinase/growth factor signaling pathway. A number of small molecule tyrosine kinase inhibitors (TKIs) have now been approved for the treatment of non-small cell lung cancers (NSCLC), including those targeted against epidermal growth factor receptor, anaplastic lymphoma kinase, and ROS1.

  • Sounds like a fancy #BsAbs technique! Saving 6-18 months of development time and reducing manufacturing costs by ~90%, WuXiBody™ platform enables almost any monoclonal antibody (mAb) sequence pair to be assembled into the bispecific construct (bispecific monoclonal antibody, #BsMAbs, #BsAbs) and its unique structural flexibility makes the platform convenient to build various formats with different valency (e.g., 2, 3 or 4 binding sites).

  • Welcome to attend ASCO-2020 #Janssen Oncology Virtual Newsroom to receive the latest result of our 4 cancer therapy pipelines: JNJ-4528 BCMA-directed CAR-T therapy Phase 1b/2 study in #multiple_myeloma; ERLEADA®(apalutamide) Phase 3 study in non-metastatic castration-resistant #prostate_cancer; and Phase 1 study of amivantamab (EGFRxMET bispecific antibody) in non-small cell #lung_cancer; and teclistamab (BCMAxCD3 bispecific antibody) in #multiple_myeloma

  • A recent Nature paper profiled lymphocytes subsets and major cytokines in a cohort of 326 patients. They found that decline of T cells, but not B cell, and elevated IL-6 correlated with disease severity. It explained why remdesivir, an antiviral drug target viral replication machinery, works better as early treatment. The reason is that the virus itself is not the only one that we are dealing with. Another paper in Cell showed that SARS-CoV-2 caused a unique signature in immune response (e.g. low IFN-I and III), compared to flu or RSV. Interestingly, the immune responses also vary with the amount of inoculated viruses. The paper also mentioned that the cytokine release syndrome is similar to a complication following CAR T treatment. The “new norm” for immunology and virology field might be to study the relations between virological activity and cytokine storm and unique immune response.

  • Binimetinib (Mektovi) is a potent and selective oral mitogen-activated protein kinase 1/2 (MEK 1/2) inhibitor together with Encorafenib (small molecule FDA approved BRAF inhibitor). On June 27, 2018, the Food and Drug Administration approved the combination of Encorafenib and binimetinib combination for patients with unresectable or metastatic melanoma with the BRAF V600E or V600K mutations. Binimetinib, non-competitive with ATP, binds to and inhibits the activity of MEK1/2. The inhibition of MEK1/2 prevents the activation of MEK1/2-dependent effector proteins and transcription factors which can result in the inhibition of growth factor-mediated cell signaling, lead to the inhibition of tumor cell proliferation and an inhibition in the production of various inflammatory cytokines including IL1, IL6 and TNF. MEK1/2 are themselves threonine and tyrosine kinases that possess a dual specificity. They subsequently contribute critically to the activation of the RAS/RAF/MEK/ERK pathway and are typically upregulated in a number of different tumor cell types.

  • Methotrexate is an antifolate antimetabolite used in the treatment of rheumatoid arthritis and cancer. Methotrexate is taken up into the cell by human reduced folate carriers (SLC19A1). In the cytoplasm, methotrexate is polyglutamated by folylpolyglutamate synthase (FPGS), which enhances its retention inside the cell. Both methotrexate and methotrexate-polyglutamate inhibit dihydrofolate reductase (DHFR), an enzyme that catalyzes the conversion of dihydrofolate into tetrahydrofolate, which is the active form of folic acid. Tetrahydrofolate is involved in many single-carbon transfer reactions, including the synthesis of DNA and RNA nucleotides. Inhibition of dihydrofolate reductase (DHFR) causes depletion of intracellular tetrahydrofolate, which has a cytotoxic effect, especially on rapidly dividing cells. Methotrexate-polyglutamate further inhibits de novo purine synthesis and thymidylate synthase, which contribute to methotrexate’s cytotoxic effects.

  • Acute hepatic porphyrias are monogenic autosomal dominant hereditary disorders involving deficiencies in heme synthesis pathway in liver hepatocytes. 5-aminolevulinic acid synthase (ALAS1) is controlled via a negative feedback loop by heme in the liver. low circulating levels of heme caused by genetic mutation stimulates the up-regulation of #ALAS1. The over-expression of ALAS1, in combination with downstream enzyme deficiencies, leads to the over-production and accumulation of toxic heme intermediates and cause acute hepatic porphyrias. Givosiran is a double-stranded small interfering RNA (siRNA) directed at ALAS1 mRNA in hepatocytes. It is covalently bound to a ligand containing three N-acetylgalactosamine (#GalNAc) residues that facilitate uptake into hepatocytes via asialoglycoprotein receptors (#ASPGRs), which are highly expressed on the cell surface of hepatocytes. Following endocytosis into hepatocytes, the antisense strand of givosiran is loaded into an enzyme complex called the RNA-induced silencing complex (#RISC), which uses the antisense strand to seek out and cleave the complementary mRNA to preventing the synthesis of the ALAS1 enzyme and leading to reduced circulating levels of neurotoxic heme intermediates.

  • Tazemetostat is a FDA approved small molecule methyltransferase inhibitor for the treatment of epithelioid sarcoma. #EZH2 is a methyltransferase subunit of the polycomb repressive complex 2 (PRC2) which catalyzes multiple methylations of lysine 27 on histone H3 (H3K27). Trimethylation of this lysine inhibits the transcription of genes associated with cell cycle arrest. #PRC2 is antagonized by the switch/sucrose non-fermentable (SWI/SNF) multiprotein complex. EZH2 over-expressed in lots of human cancers. Abnormal activation of EZH2 or loss of function mutations in SWI/SNF lead to hyper-trimethylation of #H3K27 and further leads to cancer cell de-differentiation which is a gain of cancer stem cell-like properties. de-differentiation can allow for cancer cell proliferation and exhibited worse outcome.

  • Pimodivir (VX-787, JNJ-63623872) is an antiviral drug which was developed as a treatment for influenza. It acts as an inhibitor of influenza virus polymerase basic protein 2, and has shown promising results in Phase II clinical trials.[1][2][3]

  • JNJ-68284528 (LCAR-B38M) is an investigational chimeric antigen receptor T cell (CAR-T) therapy for the treatment of patients with relapsed or refractory multiple myeloma. The design comprises a structurally differentiated CAR-T with two BCMA-targeting single domain antibodies. In December 2017, Janssen entered into an exclusive worldwide license and collaboration agreement with Legend Biotech to develop and commercialize JNJ-68284528 (LCAR-B38M). In May 2018, Janssen initiated a Phase 1b/2 trial (NCT03548207) to evaluate the efficacy and safety of JNJ-68284528 in adults with relapsed or refractory multiple myeloma, informed by the LEGEND-2 study results.

  • On April 20, 2020 , FDA approved #Pemazyre (pemigatinib) for the treatment of #cholangiocarcinoma with a fibroblast growth factor receptor 2 #FGFR2 fusion or other rearrangement. Early in 2019, FDA just approved Janssen’s #Balversa (erdafitinib), a small molecule from #Janssen, for the treatment of bladder cancer with FGFR2 or FGFR3 mutation. We expect that FGFR inhibitor provide more opportunity for other cancers. FGFR signaling pathway will be activated by FGF binds to the extracellular ligand-binding domain of the receptor and then FGFRs dimerize, autophosphorylate the tyrosine residue in the intracellular tyrosine-kinase domain, leading to the activation of the tyrosine kinase. Downstream cascades involve phosphorylation of multiple intracellular signalling proteins, such as PI3K-AKT and RAS-MAPK, and phospholipase Cγ. FGFR-mediated pathway ultimately promotes cell growth, differentiation and survival. FGFRs are not constitutively active in normal cells. However, FGFR alterations in certain tumor can lead to constitutive FGFR activation and aberrant FGFR signaling, supporting the proliferation of cancer cells.

  • Atezolizumab (Tecentriq), is a fully humanized monoclonal antibody of IgG1 isotype against the protein programmed cell death-ligand 1 #PDL1). Atezolizumab could prevent the interaction between PD-L1 and PD-1, removing inhibition of immune responses seen in some cancers. This medication is reserved for patients whose tumors express PD-L1, cannot receive platinum based chemotherapy, or whose tumors do not respond to platinum based chemotherapy. Atezolizumab was granted FDA approval on 18/10/2016. Atezolizumab blocks the interaction of PDL1 with programmed cell death protein 1 #PD1 and #CD80 receptors. PD-L1 can be highly expressed on certain tumors, which is thought to lead to reduced activation of immune cells (cytotoxic T-cells, #CTL) that might otherwise recognize and attack the cancer. It is one of several ways to block inhibitory signals related to T-cell activation, a more general strategy known as “immune checkpoint inhibition” For some cancers #bladderr) the probability of benefit is related to PD-L1 expression, but most cancers with PD-L1 expression still do not respond, while many (about 15%) without PD-L1 expression do respond. even though, PD-L1 high-expression was still used as the biomarker to select cancer patient for the treatment.

  • Infliximab #Remicade is a chimeric monoclonal antibody to TNF-α. it is a medication used to treat a number of autoimmune diseases including Crohn’s disease, ulcerative colitis, rheumatoid arthritis, ankylosing spondylitis, psoriasis, psoriatic arthritis, and Behçet’s disease. In rheumatoid arthritis, #infliximab seems to work by preventing #TNFα from binding to its receptor in the cell. TNF-α inhibitors are a group of medicines that suppress the body’s natural response to TNF, a protein produced by white blood cells that is involved in early #inflammatory events. While after injury or in certain conditions inflammation is a normal, healthy response, inflammatory disorders that result in the immune system attacking the body’s own tissues may cause abnormal inflammation, which results in chronic pain, redness, swelling, stiffness, and damage to normal tissues. By binding to both the soluble subunit and the membrane-bound precursor of TNF-α, infliximab disrupts the interaction of TNF-α with its receptors and may also cause lysis of cells that produce TNF-α

  • Abciximab is a glycoprotein IIb/IIIa receptor antagonist (platelet aggregation inhibitor) and mainly used during and after coronary artery procedures like angioplasty to prevent platelets from sticking together and causing thrombus (blood clot) formation within the coronary artery. It is a glycoprotein IIb/IIIa inhibitor. #Abciximab is made from the Fab fragments of an immunoglobulin that targets the glycoprotein IIb/IIIa receptor on the platelet membrane. In medicine, glycoprotein IIb/IIIa (GPIIb/IIIa, also known as integrin αIIbβ3, #ITGA2B and #ITGA3, is an integrin complex found on platelets. It is a receptor for fibrinogen and von Willebrand factor and aids platelet activation. it is located in chr:17-q21.32 region. What’s more, #ITGB3, ITGA2B, ITGA3B, C1R, C1QA, C1QB, C1QC, FCGR3A, C1S, FCGR1A, FCGR2A, FCGR2B, FCGR2C and #VTN are involved in the mechisizm of Abciximab

  • On 05/15/2020, FDA approved the combination of nivolumab (OPDIVO®, 2014, #PD1) plus ipilimumab (YERVOY®, 2011, #CTLA4) as first-line treatment for patients with metastatic non-small cell lung cancer whose tumors express PD-L1(≥1%) and no epidermal growth factor receptor #EGFR or anaplastic lymphoma kinase #ALK genomic aberrations. PD-L1 #immunohistochemistry should be used to select patients with NSCLC for treatment with nivolumab plus ipilimumab. Nivolumab is a fully human IgG4 antibody targeting the immune checkpoint programmed death receptor-1 (PD-1) which was produced entirely in mice and grafted onto human kappa and IgG4 Fc region with the mutation #S228P for additional stability and reduced variability. #Ipilimumab is a fully humanized IgG1 monoclonal antibody that blocks cytotoxic T lymphocyte antigen-4 #CTLA4. Blocking CTLA-4 removes an inhibitory signal from reducing the activity of T lymphocytes.

  • labeled indications and off-label indications: If the #FDA determines that there is enough evidence to approve the drug for the indication (treatment of the disease), the indication becomes a #labeled indication for the drug. Once a drug has been approved by the FDA for an indication and then marketed for that indication, physicians are allowed to prescribe the drug for any other indication (treatment for other diseases or conditions) if there is reasonable scientific evidence that the drug is effective for that indication. These uses that have not been approved by the FDA are the #off-label indications. In one 2006 study of off-label prescribing of common drugs, Randall Stafford found off-label use accounted for 21% of all prescriptions and 73% of these uses had little or no scientific support. Drugs approved for #depression, #schizophrenia and #seizures were the most likely to be used off-label without adequate scientific support for other conditions.

  • The HER2 (ERBB2) gene usually amplified/overexpressed in gastroesophageal, stomach and breast cancers. #Trastuzumab is a monoclonal antibody targeting HER2, inducing an immune-mediated response that causes internalization and downregulation of HER2. It may also upregulate cell cycle inhibitors such as #p21Waf1 and p27. It is specifically used for cancer that is HER2 receptor positive. In cancer cells the #HER2 can be expressed up to 100 times more than normal cells. HER2 extends across the cell membrane and carries signals from outside the cell to the inside. Signaling compounds called mitogens arrive at the cell membrane, and bind to the extracellular domain of the HER family of receptors and then activate several different biochemical pathways including #PI3K/Akt and #MAPK pathway that can promote cell proliferation and the growth of blood vessels to nourish the tumor. Resistance to the treatment develops rapidly and 70% of HER2+ patients do not respond to treatment. #HerceptinR is the first database developed to understand herceptin resistance that can be used for designing herceptin sensitive biomarkers. A mechanism of resistance involves failure to downregulate p27 as well as suppressing #p27 translocation to the nucleus, enabling cdk2 to induce cell proliferation.

  • FDA Updates #Purple_Book_Database of FDA-Licensed Biological Products. Today (05/12/2020), FDA is releasing an update to the Purple Book: #Database of FDA-Licensed Biological Products to add all FDA-licensed, biological products regulated by the Center for Drug Evaluation and Research (#CDER) including biological products approved in new drug applications (#NDAs) that were deemed to be licenses under section 351 of the Public Health Service Act on March 23, 2020 (transition biological products). This release also includes additional downloadable report features. #Historical reports will now include a section highlighting changes made during the previous month – for example, the monthly data download will include a section at the top highlighting all new/updated products during the selected month.

  • 05/08/2020, FDA Approves Selpercatinib for Lung and Thyroid Cancers with RET Gene Mutations or Fusions. Selpercatinib is a selective RET kinase inhibitor. RET is a transmembrane receptor protein tyrosine kinase present on the surface of a number of tissues types including the nervous system, adrenal medulla and thyroid. RET fusions occur in 1-2% of NSCLC. Like other oncogenic driver mutations in lung cancer, patients with RET fusions are typically associated with younger age, female gender, non-smokers and Asian ethnicity. Retevmo may affect both tumor cells and healthy cells, which can result in side effects. RET fusions or rearrangements are somatic juxtapositions of 5′ sequences from other genes with 3′ RET sequences encoding tyrosine kinase. The most common RET fusions are CDCC6-RET and NCOA4-RET in PTC and KIF5B-RET in NSCLC. Oncogenic RET rearrangements in NSCLC result in constitutive activation of RET and consistently preserve the RET tyrosine kinase domain.

  • 04/28/2020, FDA granted accelerated approval to a new dosing regimen of #400 mg every 6 weeks for #pembrolizumab (humanized PD-1) across all currently approved adult indications, in addition to the current #200 mg every 3 weeks dosing regimen. Pembrolizumab is a therapeutic antibody that binds to and blocks #PD_1 located on #lymphocytes. This receptor is generally responsible for preventing the immune system from attacking the body’s own tissues; it is a so-called immune checkpoint. Many cancers make proteins that bind to PD-1 to escape immune cell surveillance. Inhibiting #PD-1 on the lymphocytes prevents this, allowing the immune system to target and destroy cancer cells; this same mechanism also allows the #immune system to attack the body itself, and checkpoint inhibitors like pembrolizumab have immune-dysfunction side effects as a result. Tumors that have mutations that cause impaired DNA mismatch repair, which often results in microsatellite instability #msi), tend to generate many mutated proteins that could serve as tumor antigens; pembrolizumab appears to facilitate clearance of such tumor by immune system, by preventing the self-checkpoint system from blocking the clearance collapse.

  • Synthetic lethality has been successfully applied in cancer drug development. #BRCA and #PARP is an classic example. Cancer cells with both BRCA1/2 and PARP loss-of-function will induce the apoptosis and cell death. Olaparib is a #PARP inhibitor, inhibiting poly ADP ribose polymerase #PARPP), an enzyme involved in DNA repair. It acts against cancers in people with hereditary #BRCA1 or #BRCA2 mutations, which include some ovarian, breast, and prostate cancers. Recently, FDA approved Olaparib plus Bevacizumab as maintenance treatment for ovarian cancer. Bevacizumab is a recombinant humanized monoclonal antibody that blocks #angiogenesis by inhibiting vascular endothelial growth factor A #VEGFA which is a growth factor protein that stimulates #angiogenesis in a variety of diseases. #VEGFA is upregulated in many tumors and its expression is correlated with tumor development and is a target in many developing cancer therapeutics.

  • On May 1, 2020, FDA approved #Darzalex_Faspro™) for the treatment of #multiple_myeloma in adult patients. Darzalex Faspro™ is a new #subcutaneous formulation that contains daratumumab (a #CD38-directed cytolytic antibody) and hyaluronidase (an endoglycosidase). The new formulation is administered over approximately 3-5 minutes compared with the intravenous (IV) formulation of daratumumab #Darzalex®) that is administered over hours. #Daratumumab is an IgG1k monoclonal antibody directed against #CD38 which is overexpressed in multiple myeloma. Daratumumab binds to CD38, causing cells to #apoptose via antibody-dependent cellular #cytotoxicity or complement-dependent cytotoxicity.

  • Johnson & Johnson population analytics team are still hiring Computational #Genomics Scientists (CGS). If you have a strong computational genomics and bioinformatics background and want to join a company with a pipeline in high-growth mode. Welcome to join our team in #Janssen Research & Development, Johnson & Johnson! We will work together to build a best-in-class target identification and validation engine #TIDVALEE) to feed our discovery pipeline and to identify novel disease targets and drug targets from genetic and epigenetics data including #UKBB, #FinnGen, #eMERGE, JNJ-RNAseq and other omics data to evaluate the drug safety under the frame of precision medicine leveraging human genetics and advance statistical approach. We encourage to publish what you have discovered in the #GWAS, #PheWAS and #FunctionalGenomics study to accelerate your career both in academia and industry. Again, join us if you have strong skills on computational genomics, #programming and data analysis skills. Scientist and Senior Scientist positions are available.

  • In 2019, Johnson & Johnson worked together with National Institute of Allergy and Infectious Diseases #NIAIDD) and Bill & Melinda Gates Foundation #BMGFF) started #Mosaico project (phase 3 clinical trail) to test #HIV vaccine in man. Before that, In 2017, Johnson & Johnson started #Imbokodo project (Phase 2b) to test HIV vaccine in women. Now, we are doing our best to work on #COVID10 vaccine development. In the above 2 HIV vaccine projects, HIV #vaccine components were designed to induce immune responses against a wide variety of global HIV strains. For example, all #Imbokodo participants will receive vaccinations at 4 timepoints over one year and will be randomly assigned to either the experimental vaccine regimen or placebo. The experimental regimen includes 4 doses of the quadrivalent mosaic vaccine. The final 2 doses will be given together with doses of an HIV protein, clade C #gp140, and an aluminum phosphate adjuvant to boost immune responses. Participants will be followed for 2 years. HIV Vaccine Trials Network #HVTNNN) has tried numerous vaccines, however, the majority are failed. Interested in HIV vaccine study of #Janssen, check the following website here:

  • Johnson & Johnson population analytics team are still hiring Genetic Scientists. If you have a strong Biomedical informatics, #EHR #EMR, Biomedical data science or Genetic Epidemiology or Bio-statistics background and want to join a company with a pipeline in high-growth mode. Welcome to join our team in #Janssen Research & Development, Johnson & Johnson! We will work together to identify novel disease targets and drug targets from population genetic data including #UKBB, #FinnGen, #EstonianGenmics, #eMERGE, #ROSMAP, #HNP and to evaluate the drug safety under the frame of precision medicine leveraging human genetics and advance statistical approach. We have raw data therefore advance analyses are supported such as IBD, phasing and haplotype-based statistical test. We encourage to publish what you have discovered in the #GWAS and #PheWAS study to accelerate your career both in academia and industry. Again, join us if you have strong skills on EHR/EMR data analysis, genetic association, causal inference and machine learning. Scientist and Senior Scientist positions are available.

  • Anakinra (Kineret) is a biopharmaceutical drug used to treat rheumatoid arthritis. It is a recombinant and slightly modified version of the human interleukin 1 receptor antagonist protein. As a recombinant, nonglycosylated human interleukin-1 receptor antagonist (IL-1Ra). It can treat rheumatoid arthritis and neonatal-onset multisystem inflammatory disease (NOMID). The difference between anakinra and the native human IL-1Ra is that anakinra has an extra methionine residue at the amino terminus. It is manufactured by using the E. coli expression system. Anakinra is composed of 153 amino acid residues. FDA approved on November 14, 2001. Anakinra binds competitively to the Interleukin-1 type I receptor (IL-1RI), thereby inhibiting the action of elevated levels IL-1 which normally can lead to cartilage degradation and bone resorption.

  • Nutraceutical products
    levocarnitine
    tryptophan
    omega-3 polyunsaturated fatty acids
    chondroitin
    glucosamine
    betaine
    ubiquinone
    glutamine
    glucosamine
    methionine
    inositol
    chondroitin
    chondroitin
    glucosamine
    methylsulfonylmethane
    lecithin
    alpha-lipoic acid
    s-adenosylmethionine
    

Bioinformatics Skills Required

1915-02-28 00:00:00 +0000

02/27/2021: Johnson & Johnson COVID-19 Vaccine Authorized by U.S. FDA For Emergency Use - First Single-Shot Vaccine in Fight Against Global Pandemic

01/26/2021: Karyopharm Gets FDA OK of Xpovio in Multiple Myeloma

  • https://m-clark.github.io/mixed-models-with-R/
  • https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2017-December/000434.html
  • https://www.bioconductor.org/help/course-materials/2015/BiocAsia2015/W3-RNASeq.html

01/26/2021: Karyopharm Gets FDA OK of Xpovio in Multiple Myeloma

01/12/2021: An Introduction to Medical Statistics interesting book: https://www-users.york.ac.uk/~mb55/intro/introcon.htm#ci

01/03/2020: https://www.fiercebiotech.com/special-report/glaxosmithkline-top-10-pharma-r-d-budgets-2019 01/01/2020: https://mp.weixin.qq.com/s/riojeB3x8CVBNzWkrvTqrA

COVID19 mRNA vaccine: https://en.wikipedia.org/wiki/Tozinameran COVID19 mRNA vaccine: https://www.mcgill.ca/oss/article/covid-19-critical-thinking-health/reassuring-data-pfizers-covid-19-vaccine

12/30/2020: Trends In US Expedited Review Programs: https://pharmaintelligence.informa.com/~/media/informa-shop-window/pharma/2020/files/article-packs/accelerated-approvals-article-pack-us-coverage.pdf

12/29/2020: Nomenclature_of_monoclonal_antibodies: https://en.wikipedia.org/wiki/Nomenclature_of_monoclonal_antibodies 12/29/2020: Nomenclature_of_drugs: https://en.wikipedia.org/wiki/Drug_nomenclature

12/28/2020: https://www.fda.gov/drugs/new-drugs-fda-cders-new-molecular-entities-and-new-therapeutic-biological-products/novel-drug-approvals-2020 12/28/2020: http://expertmeetingziekenhuisfarmacie.nl/wp-content/uploads/IMS-Health-European-Thought-Leadership-Cell-Gene-Therapy-white-paper-20….pdf

11/30/2020: ‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures. Google’s deep-learning program for determining the 3D shapes of proteins stands to transform biology, say scientists. On protein targets considered to be moderately difficult, the best performances of other teams typically scored 75 on a 100-point scale of prediction accuracy, whereas AlphaFold scored around 90 on the same targets, says Moult. https://www.nature.com/articles/d41586-020-03348-4

11/29/2020, In a recently completed pivotal, clinical efficacy, Phase 3 trial, M-001 failed to demonstrate a statistically significant difference between the vaccinated and placebo groups in reduction of flu illness and severity, and therefore failed to meet both the primary and secondary efficacy endpoints.

Osteoarthritis therapeutics market is expected to grow from USD 6.8 billion in 2019 to reach USD 10.1 billion by 2024, at a CAGR of 8.1%. CAGR Calculator is free online tool to calculate compound annual growth rate for your investment over a time period. To get the CAGR value for your investment, enter the starting value or initial investment amount along with the expected ending value and the number of month or year for which you want to calulate the CAGR. Then, click on calculate button and let the online CAGR calculator calculate the value for you. This will produce the CAGR or compound annual growth rate along with compounded growth chart for your initial investment value.

11/24/2020: FDA Approves Oxlumo (lumasiran) for the Treatment of Primary Hyperoxaluria Type 1.

FDA Approves Sutab (sodium sulfate, magnesium sulfate, and potassium chloride) Tablets for Colonoscopy Preparation Bioinformaticians needed for Genomics Medicine Ireland. GMI is a recently incorporated company leading a large-scale research programme on the human genome to examine the relationship between genetics, health and disease. Our mission is to become a global Center of Excellence for omics and use our scientific strength to understand diseases of genetic origin through analysis and interpretation of the human genome empowered with rich medical and lifestyle data.

We are currently building the next stage of our bioinformatics team (GBT). GBT will analyse the ‘omics data produced at GMI, which currently includes disease cohorts such as IBD, Multiple sclerosis, Alzheimers, rare diseases and cancer. Our work will also focus on ancestry related topics, namely how population genetics can increase the power of disease analysis. GBT will interact with GMI’s very strong IT infrastructure, clinical partnerships and research teams, which facilitate and provide an integrated framework for our bioinformatics analysis. We are building a team of cognitively diverse people, that will feed off each other to find GMI’s analytical solutions, ranging from bioinformaticians; biologists or medical doctors with knowledge of bioinformatics tools; individuals with an IT background with an enthusiasm to apply their knowledge to ’omics.

Essential Qualifications and Knowledge Some of the following: • PhD in Bioinformatics or Genomics • BSc/MSc/PhD in Computer Science/Mathematics/Statistics • Knowledge of rare, neurological, auto-immune or oncological disease research • Knowledge of analysis of genetic causes of disease • Knowledge of statistical genetics • Knowledge of Bioinformatics ‘omics and big data analysis.

Technical Expertise Some of the following: • ’Omic packages such as PLINK, Admixture, Eigensoft, NGSQC, DNAnexus, Ingenuity, Pathway Analysis software, BWA, GATK, SAMtools, ANNOVAR, Peddy • R, Python, Perl, C++, JavaScript • Bioconductor, Biopython, NumPy, SciPy, pandas • Databases and libraries such as PostgreSQL, NoSQL, Hadoop, Spark • Cloud high-performance compute with AWS/GCP • Machine Learning such as MLlib, Scikit-learn, PyTorch, Keras, TensorFlow

Preferred Experience •Several Scientific publications on ’omics or statistical genetics • Producer and/or maintainer of ’omic software publicly available • Experience in large science-driven organizations or consortia •Experience in international consortia • Participation in genetics, statistics, ’omics or bioinformatics meetings

Single-cell RNA-Sequencing (scRNA-Seq) is fast becoming a widespread technique for life science research. However, with more scRNA-Seq datasets deposited in public databases than ever before, it is important to ensure the integrity and reproducibility of the data. Find out how researchers from EMBL-EBI, University of California, Harvard Medical School, Wellcome Sanger Institute, University of Cambridge and other colleagues have put together guidelines for a minimum set of metadata needed for robust comparative analyses of scRNA-Seq. https://www.nature.com/articles/s41587-020-00744-z