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CancerScreen Panels

Highly optimized NGS panel for somatic cancer

Overview
Features & Benefits
Specification
Related Products
Resources
References
Overview
Features & Benefits
Specification
Related Products
Resources
References

Overview

CancerScreen Panel Core/50/100/400/Comprehensive

CancerScreen 패널은 Somatic Cancer와 연관 있는 것으로 알려진 765개의 유전자에 속한 유전 변이들을 검출하기 위한 패널입니다. 암종과 연관 있는 유전자들의 유전변이를 정확하게 분석하기 위해 높은 특이도와 민감도를 갖도록 개발된 패널로 비용 효율적인 분석이 가능합니다.
셀레믹스에서는 BI 분석 서비스를 제공하고 있습니다. 1차 (Primary), 2차 (Secondary), 3차 (Tertiary)의 세분화된 수준의 분석 결과를 제공할 수 있어 고객이 원하는 결과의 수준에 따라 다른 분석 결과를 제공하고 있습니다. BI에 익숙하지 않은 고객들도 별도의 세팅 없이 유전 변이 분석 결과를 얻을 수 있습니다.

CancerScreen Panels
Features & Benefits

고형암 분석에 최적화된 NGS 패널

본 패널은 최대 765개의 고형암 연관 유전자를 포함하며 RefSeq 데이터베이스에 기록된 전체 CDS 영역을 타겟 영역으로 합니다. SNV, InDel, Large InDel, CNV, Gene Rearrangements 및 MSI, TMB를 비롯해 TERT Promoter 영역의 유전 변이까지 모든 종류의 유전 변이를 한 번의 검사로 분석할 수 있습니다.

Performance Comparison with Competitor Product

  • Higher on-target ratio, uniformity, coverage at 100X compared to competitor product over the target regions including exons and introns
Performance Comparison with Competitor Product

높은 민감도와 특이도

CancerScreen 패널은 매우 높은 시퀀싱 depth를 바탕으로 낮은 빈도로 발생하나 암종에 중요하다고 알려진 유전 변이들을 정확히 검출할 수 있도록 디자인되었습니다. 독자적인 프로브 디자인 기술을 바탕으로 GC-rich 영역이나 Homologous 영역에 발생하는 유전  변이뿐만 아니라 FFPE, ctDNA와 같은 손상되거나 미량인 샘플에 대해서도 최상의 민감도와 특이도로 중요한 유전변이들을 놓치지 않고 분석할 수 있습니다.

시퀀싱 효율 극대화를 통한 비용 절감 효과

셀레믹스는 모든 NGS 패널에 대해 시약 및 프로토콜 최적화를 진행합니다. 최고의 On-target Ratio, Uniformity를 바탕으로 높은 비용 절감 효과를 누릴 수 있습니다. 더불어 독자적인 시약 개발 기술을 바탕으로 다양한 시퀀싱 플랫폼에 최적화된 NGS 패널을 제공해 드리고 있습니다.

Performance Comparison over GC-rich Regions

  • More uniform read depths over GC-rich regions compared to competitor products.
Performance Comparison over GC-rich Regions
Performance Comparison over GC-rich Regions

Specification

Gene count* 13/54/99/407/765 genes
Target size 61/197/299/1,123/2,521 kb + Rearrangement
Mutation type SNV, Indel, CNV, Rearrangement, MSI, TMB
Sample type(amount) FFPE, frozen tissue, cfDNA, RNA
Platform All sequencers from Illumina, Thermo Fisher, MGI, PacBio, and Oxford Nanopore
Bioinformatics Support ① Primary Analysis: FASTQ to annotated VCF
② Secondary Analysis: CNV, Large InDel
③ Tertiary Analysis: Clinical interpretation

Specification - Gene List

  • 13 genes | Gene count
  • 61 kb | Target Size
  • Whole CDS, Rearrangement | Target Region
ALK APC BRAF EGFR ERBB2 KRAS MET NRAS PIK3CA RET ROS1 SMAD4 TP53
  • 54 genes | Gene count
  • 197 kb | Target Size
  • Whole CDS, Rearrangement | Target Region
ABL1 AKT1 ALK APC ATM BRAF BRCA1 BRCA2 CDH1 CDK4 CDK6 CDKN2A
CSF1R CTNNB1 DDR2 EGFR ERBB2 ERBB4 ESR1 FGFR1 FGFR2 FGFR3 GNA11 GNAQ
GNAS HRAS IDH1 IDH2 JAK2 KDR KIT KRAS MAP2K1 MET MLH1 MTOR
MYC MYCN NOTCH1 NRAS NTRK1 PDGFRA PIK3CA PTCH1 PTEN PTPN11 RB1 RET
ROS1 SMAD4 SMO SRC STK11 TP53
  • 99 genes | Gene count
  • 299 kb | Target Size
  • CDS | Target Region
ABL1 AKT1 AKT2 AKT3 ALK APC ARID1A ARID1B ARID2 ATM ATRX AURKA
AURKB BARD1 BCL2 BLM BMPR1A BRAF BRCA1 BRCA2 BRIP1 CDH1 CDK4 CDK6
CDKN2A CHEK2 CSF1R CTNNB1 DDR2 EGFR EPCAM EPHB4 ERBB2 ERBB3 ERBB4 EZH2
FBXW7 FGFR1 FGFR2 FGFR3 FLT3 GNA11 GNAQ GNAS HNF1A HRAS IDH1 IDH2
IGF1R ITK JAK1 JAK2 JAK3 KDR KIT KRAS MDM2 MET MLH1 MPL
MRE11 MSH2 MSH6 MTOR MUTYH NBN NF1 NOTCH1 NPM1 NRAS NTRK1 PALB2
PDGFRA PDGFRB PIK3CA PIK3R1 PMS2 PRSS1 PTCH1 PTCH2 PTEN PTPN11 RAD50 RAD51C
RAD51D RB1 RET ROS1 SLX4 SMAD4 SMARCB1 SMO SRC STK11 SYK TERT
TOP1 TP53 VHL
  • 407 genes | Gene count
  • 1,123 kb | Target Size
  • CDS | Target Region
ABL1 ABL2 ADGRA2 AKT1 AKT2 AKT3 ALK AMER1 APC APCDD1 APEX1 APOB
APOBEC1 AR ARAF ARFRP1 ARID1A ARID1B ARID2 ASXL1 ATM ATP11B ATR ATRX
AURKA AURKB AXIN1 AXL B2M B3GAT1 BACH1 BAP1 BARD1 BCL2 BCL6 BCL9
BCOR BCR BIRC2 BIRC3 BLM BRAF BRCA1 BRCA2 BRD2 BRD3 BRD4 BRIP1
BTG1 BTK BTLA CARD11 CASP5 CASP8 CBFB CBL CD274 CDK12 CDK4 CDK6
CDK8 CDKN1A CDKN1B CDKN2A CDKN2B CDKN2C CDX2 CEBPA CHD1 CHD2 CHD4 CHEK1
CHEK2 CHUK CIC CRBN CREBBP CRKL CRLF2 CSF1R CSF2 CSF2RA CSF2RB CSNK2A1
CTCF CTLA4 CTNNA1 CTNNB1 CUL3 CUL4A CUL4B CXCL10 CXCL11 CXCL9 CXCR3 CYLD
CYP17A1 DAXX DCUN1D1 DDR2 DICER1 DIS3 DNMT1 DNMT3A DOCK2 DOT1L EGFR ELMO1
EML4 EMSY EP300 EPHA3 EPHA5 EPHA6 EPHA7 EPHB1 EPHB4 EPHB6 ERBB2 ERBB3
ERBB4 ERCC1 ERCC2 ERG ERRFI1 ESR1 ETV1 ETV4 ETV5 ETV6 EWSR1 EYA2
EZH2 FANCA FANCC FANCD2 FANCE FANCF FANCG FANCI FANCL FANCM FAS FAT1
FAT3 FBXW7 FGF1 FGF10 FGF12 FGF14 FGF19 FGF2 FGF23 FGF3 FGF4 FGF6
FGF7 FGFR1 FGFR2 FGFR3 FGFR4 FH FLCN FLT1 FLT3 FLT4 FOXA1 FOXL2
FOXO3 FOXP3 FRS2 FUBP1 GABRA6 GAS6 GATA1 GATA2 GATA3 GATA4 GATA6 GID4
GLI1 GNA11 GNA13 GNAQ GNAS GRIN2A GRM3 GSK3B GUCY1A2 GZMA GZMB GZMH
H3F3A HGF HIST1H3B HNF1A HOXA3 HRAS HSD3B1 HSP90AA1 IDH1 IDH2 IDO1 IDO2
IFITM1 IFITM3 IFNA1 IFNB1 IFNG IGF1 IGF1R IGF2 IGF2R IKBKE IKZF1 IL12A
IL12B IL2 IL23A IL6 IL7R INHBA INPP4B INSR IRF2 IRF4 IRS2 ITGAE
ITK JAK1 JAK2 JAK3 JUN KAT6A KDM5A KDM5C KDM6A KDR KEAP1 KEL
KIT KLF4 KLHL6 KMT2A KMT2B KMT2C KNSTRN KRAS LAG3 LMO1 LRP1B LRP6
LTK LYN LZTR1 MAGI2 MAGOH MAML1 MAP2K1 MAP2K2 MAP2K4 MAP3K1 MAP3K13 MAPK1
MAX MCL1 MDM2 MDM4 MED12 MEF2B MEN1 MET MITF MLH1 MPL MRE11
MSH2 MSH6 MTOR MUTYH MYB MYC MYCL MYCN MYD88 MYO18A NCOA3 NCOR1
NF1 NF2 NFE2L2 NFKBIA NOTCH1 NOTCH2 NOTCH3 NOTCH4 NPM1 NRAS NSD1 NSD3
NTRK1 NTRK2 NTRK3 NUP93 NUTM1 PAK3 PAK5 PALB2 PARP1 PARP2 PARP3 PARP4
PAX5 PBRM1 PDCD1 PDCD1LG2 PDGFRA PDGFRB PDK1 PGR PHF6 PHLPP2 PIK3C2B PIK3C3
PIK3CA PIK3CB PIK3CG PIK3R2 PKHD1 PLCG1 PLCG2 PMS2 PNP PNRC1 POLD1 POLE
PPARG PPP2R1A PRDM1 PREX2 PRF1 PRKAR1A PRKCI PRKDC PRPF40B PRSS8 PTCH1 PTCH2
PTEN PTK2 PTPN11 PTPRC PTPRD QKI RAB35 RAC1 RAC2 RAD17 RAD50 RAD51
RAD52 RAD54L RAF1 RANBP2 RARA RB1 RBM10 REL RET RHEB RHOA RHOB
RICTOR ROBO1 ROBO2 ROS1 RPA1 RPS6KB1 RPTOR RUNX1 RUNX1T1 RUNX3 SDHA SDHB
SDHC SDHD SEMA3A SEMA3E SET SETBP1 SETD2 SF3A1 SF3B1 SH2B3 SKP2 SLIT2
SMAD2 SMAD3 SMAD4 SRSF2 SRSF7 STAG2 STAT3 STAT4 TERT TET2 TP53  
  • 765 genes (697 genes for DNA, 68 genes for RNA) | Gene count
  • 2.32 Mb (DNA), 201 Kb (RNA) | Target Size
  • CDS, Hotspot variant, UTR, Intronic, Intergenic regions, and MSI markers | Target Region

[DNA – Gene List]

ABL1 ABL2 ABRAXAS1 ACVR1 ACVR1B ACVR2A ADAM29 ADGRA2 ADTRP AKT1 AKT2 AKT3
ALK ALOX12B ALOX15B AMER1 ANKRD11 ANKRD26 APC APCDD1 APEX1 APOB APOBEC1 APOBEC3A
APOBEC3B AR ARAF ARFRP1 ARID1A ARID1B ARID2 ARID5B ASTE1 ASXL1 ASXL2 ATM
ATP11B ATR ATRX AURKA AURKB AXIN1 AXIN2 AXL B2M B3GAT1 BACH1 BAP1
BARD1 BAX BBC3 BCL10 BCL2 BCL2A1 BCL2L1 BCL2L11 BCL2L2 BCL6 BCL9 BCOR
BCORL1 BCR BEX5 BIRC2 BIRC3 BLM BMPR1A BRAF BRCA1 BRCA2 BRD2 BRD3
BRD4 BRIP1 BTG1 BTK BTLA CADM1 CALR CARD11 CASP5 CASP8 CBFB CBL
CCDC150 CCDC168 CCDC43 CCL2 CCL4 CCN6 CCND1 CCND2 CCND3 CCNE1 CD27 CD274
CD276 CD28 CD3D CD3E CD3G CD4 CD40 CD44 CD74 CD79A CD79B CD8A
CDC42 CDC73 CDH1 CDH2 CDH20 CDH5 CDK12 CDK4 CDK6 CDK8 CDKN1A CDKN1B
CDKN2A CDKN2B CDKN2C CDX2 CEBPA CENPA CHD1 CHD2 CHD4 CHEK1 CHEK2 CHUK
CIC COLEC12 COP1 CRBN CREBBP CRK CRKL CRLF2 CSF1R CSF2 CSF2RA CSF2RB
CSF3R CSNK1A1 CSNK2A1 CTCF CTLA4 CTNNA1 CTNNB1 CUL3 CUL4A CUL4B CUX1 CXCL10
CXCL11 CXCL9 CXCR3 CXCR4 CYLD CYP17A1 CYP4Z2P DAXX DCUN1D1 DDHD1 DDR2 DDX41
DEFB105A DHX15 DICER1 DIS3 DNAJB1 DNMT1 DNMT3A DNMT3B DOCK2 DOCK3 DOT1L E2F3
EED EGFL7 EGFR EIF1AX EIF4A2 EIF4E ELMO1 ELOC EML4 EMP1 EMSY EP300
EPCAM EPHA3 EPHA5 EPHA6 EPHA7 EPHB1 EPHB4 EPHB6 ERBB2 ERBB3 ERBB4 ERCC1
ERCC2 ERCC3 ERCC4 ERCC5 ERG ERRFI1 ESR1 ETS1 ETV1 ETV4 ETV5 ETV6
EWSR1 EYA2 EZH2 FANCA FANCC FANCD2 FANCE FANCF FANCG FANCI FANCL FANCM
FAS FAT1 FAT3 FBXW7 FGF1 FGF10 FGF12 FGF14 FGF19 FGF2 FGF23 FGF3
FGF4 FGF5 FGF6 FGF7 FGF8 FGF9 FGFR1 FGFR2 FGFR3 FGFR4 FH FLCN
FLI1 FLT1 FLT3 FLT4 FOXA1 FOXL2 FOXO1 FOXO3 FOXP1 FOXP3 FRS2 FUBP1
FYN GABRA6 GAS6 GATA1 GATA2 GATA3 GATA4 GATA6 GEN1 GID4 GLI1 GNA11
GNA13 GNAQ GNAS GPS2 GREM1 GRIN2A GRM3 GSK3B GUCY1A2 GZMA GZMB GZMH
H1-2 H2AC13 H2BC5 H3-3A H3-3B H3-4 H3-5 H3C1 H3C11 H3C12 H3C13 H3C14
H3C15 H3C2 H3C3 H3C4 H3C6 H3C7 H3C8 HGF HLA-A HLA-B HLA-C HLA-DRA
HLA-E HLA-F HLA-G HNF1A HNRNPK HOXA3 HOXB13 HRAS HSD3B1 HSP90AA1 ICOSLG ID3
IDH1 IDH2 IDO1 IDO2 IFITM1 IFITM3 IFNA1 IFNB1 IFNG IFNGR1 IGF1 IGF1R
IGF2 IGF2R IKBKE IKZF1 IL10 IL12A IL12B IL2 IL23A IL6 IL7R INHA
INHBA INPP4A INPP4B INSR IRF2 IRF4 IRS1 IRS2 ITGAE ITK JAK1 JAK2
JAK3 JUN KAT6A KDM5A KDM5C KDM6A KDR KEAP1 KEL KIF5B KIT KLF4
KLHL6 KMT2A KMT2B KMT2C KMT2D KNSTRN KRAS LAG3 LAMP1 LATS1 LATS2 LMO1
LRP1B LRP6 LTK LTN1 LYN LZTR1 MAGI2 MAGOH MALT1 MAML1 MAP2K1 MAP2K2
MAP2K4 MAP3K1 MAP3K13 MAP3K14 MAP3K4 MAPK1 MAPK3 MAX MCL1 MDC1 MDM2 MDM4
MED12 MEF2B MEF2C MEN1 MET MGA MITF MLH1 MLLT3 MPL MRE11 MSH2
MSH3 MSH6 MST1 MST1R MTMR11 MTOR MTR MUTYH MYB MYC MYCL MYCN
MYD88 MYL1 MYLK MYO18A MYOD1 NAB2 NBN NCOA3 NCOR1 NDUFC2 NEGR1 NF1
NF2 NFE2L2 NFKBIA NKX2-1 NKX2-8 NKX3-1 NOMO1 NOTCH1 NOTCH2 NOTCH3 NOTCH4 NPM1
NRAS NRG1 NSD1 NSD3 NTRK1 NTRK2 NTRK3 NUP93 NUTM1 PAK1 PAK3 PAK5
PALB2 PARP1 PARP2 PARP3 PARP4 PAX3 PAX5 PAX7 PAX8 PBRM1 PCDH17 PDCD1
PDCD1LG2 PDE4D PDGFRA PDGFRB PDK1 PDPK1 PGR PHF6 PHLPP2 PHOX2B PIK3C2B PIK3C2G
PIK3C3 PIK3CA PIK3CB PIK3CD PIK3CG PIK3R1 PIK3R2 PIK3R3 PIM1 PKHD1 PLCG1 PLCG2
PLK2 PMAIP1 PMS1 PMS2 PNP PNRC1 POLD1 POLE PPARG PPM1D PPP2R1A PPP2R2A
PPP6C PRDM1 PREX2 PRF1 PRKAR1A PRKCI PRKDC PRKN PRPF40B PRSS8 PTCH1 PTCH2
PTEN PTK2 PTPN11 PTPRC PTPRD PTPRS PTPRT PUS3 QKI RAB35 RAC1 RAC2
RAD17 RAD21 RAD50 RAD51 RAD51B RAD51C RAD51D RAD52 RAD54L RAF1 RANBP2 RARA
RASA1 RB1 RBM10 RBMXL1 RECQL4 REL RET RFX1 RHEB RHOA RHOB RICTOR
RIT1 RNF19B RNF43 ROBO1 ROBO2 ROS1 RPA1 RPS6KA4 RPS6KB1 RPS6KB2 RPTOR RUNX1
RUNX1T1 RUNX3 RYBP SDHA SDHAF2 SDHB SDHC SDHD SEC31A SEMA3A SEMA3E SET
SETBP1 SETD2 SF3A1 SF3B1 SH2B3 SH2D1A SHQ1 SKP2 SLC22A9 SLIT2 SLITRK3 SLX4
SMAD2 SMAD3 SMAD4 SMAP1 SMARCA1 SMARCA4 SMARCB1 SMARCD1 SMC1A SMC3 SMO SNCAIP
SOCS1 SOX10 SOX17 SOX2 SOX9 SPEN SPOP SPTA1 SRC SRSF1 SRSF2 SRSF7
STAG1 STAG2 STAT3 STAT4 STAT5A STAT5B STC1 STK11 STK40 SUFU SUZ12 SYK
TACC3 TAF1 TBX22 TBX3 TCF3 TCF7L2 TENT5C TERC TERT TET1 TET2 TFE3
TFRC TGFBR1 TGFBR2 TIAF1 TIGIT TIPARP TMEM127 TMPRSS2 TNF TNFAIP3 TNFRSF14 TNFRSF18
TNFRSF4 TNFSF13B TNKS TNKS2 TOP1 TOP2A TP53 TP63 TRAF2 TRAF7 TRRAP TSC1
TSC2 TSHR U2AF1 U2AF2 USP9X VEGFA VHL VSIR VTCN1 WNT1 WT1 WWP1
XBP1 XIAP XPO1 XRCC2 XRCC3 YAP1 YES1 ZBTB2 ZBTB7A ZFHX3 ZNF217 ZNF703
ZRSR2                      

 

[RNA – Gene List]

ABL1 AKT3 ALK AR AXL BAIAP2L1 BCL2 BRAF BRCA1 BRCA2 CCDC6 CD74
CDK4 CSF1R EGFR EML4 ERBB2 ERG ESR1 ETS1 ETV1 ETV4 ETV5 ETV6
EWSR1 FGFR1 FGFR2 FGFR3 FGFR4 FLI1 FLT1 FLT3 JAK2 KDR KIF5B KIT
KMT2A LMNA MET MLLT3 MSH2 MYC NCOA4 NOTCH1 NOTCH2 NOTCH3 NRG1 NTRK1
NTRK2 NTRK3 PAX3 PAX7 PAX8 PDGFRA PDGFRB PIK3CA PPARG RAF1 RET ROS1
RPS6KB1 SEPTIN14 SLC34A2 SLC45A3 TACC3 TFG TMPRSS2 TPM3        

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FDA 승인된 약물과 연관 있는 것으로 알려진 유전변이 검출을 위한 패널로 약물과 연관성이 높은 주요 유전자를 폭넓게 커버하는 패널

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Celemics Analysis Service

CAS

셀레믹스에서 제공하는 BI 분석 서비스로 다양한 수준의 분석 결과 제공 가능

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Resources

Technical Resources

[Product Sheet] Celemics CancerScreen Core/50/100/400

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[Product Sheet] Celemics CancerScreen Comprehensive

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[Product Sheet] Celemics CancerScreen Focus

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[Product Sheet] Celemics CancerScreen CUP(Cancer of Unknown Primary)

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Celemics Target Enrichment Panel Overview

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Celemics Products & Services

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Safety Data Sheets

최신 MSDS 파일이 필요하시면 ‘Contact Us‘를 통해 문의 주시기 바랍니다.

MSDS_CancerScreen Panels_Illumina

MSDS_CancerScreen Panels_Thermo Fisher

MSDS_CancerScreen Panels_MGI

References

The clinical relevance of surgical specimens for RNA sequencing in lung cancer: a cohort study

Frontiers in Oncology

The clinical relevance of surgical specimens for RNA sequencing in lung cancer: a cohort study

Eom, J. S., Kim, S. H., Kim, K., Kim, A., Ahn, H. Y., Mok, J., … & Kim, M. H. (2024). The clinical relevance of surgical specimens for RNA sequencing in lung cancer: A cohort study. Frontiers in Oncology, 14, 1462519.

 

10.3389/fonc.2024.1462519


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Varlitinib and Paclitaxel for EGFR/HER2 Co-Expressing Advanced Gastric Cancer: A Multicenter Phase Ib/II Study (K-MASTER-13)

Cancer Research and Treatment

Varlitinib and Paclitaxel for EGFR/HER2 Co-Expressing Advanced Gastric Cancer: A Multicenter Phase Ib/II Study (K-MASTER-13)

Koo DH, Jung M, Kim YH, Jeung HC, Zang DY, Bae WK, Kim H, Kim HS, Lee CK, Kwon WS, Chung HC. Varlitinib and Paclitaxel for EGFR/HER2 Co-Expressing Advanced Gastric Cancer: a Multicenter Phase Ib/II Study (K-MASTER-13). Cancer Research and Treatment. 2024 Apr 29.

 

10.4143/crt.2023.1324


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Summary | celemics publications


#Oncology


#ctDNA Sample


# AlphaLiquid® 100 Panel

Purpose

Varlitinib is a pan-human epidermal growth factor receptor (HER) inhibitor targeting epidermal growth factor receptor (EGFR), HER2, and HER4. We present a phase Ib/II study of a combination of varlitinib and weekly paclitaxel as a second-line treatment for patients with EGFR/HER2 co-expressing advanced gastric cancer (AGC).

Result

Genomic alteration landscape in circulating tumor DNA analysis according to the progression-free survival (PFS), overall survival (OS), and EGFR/HER2 immunohistochemical expression (n=15).


Conclusion

A combination of varlitinib and paclitaxel displayed manageable toxicity and modest antitumor activity in patients with EGFR/HER2 co-expressing AGC who progressed after first-line chemotherapy.

Method

The circulating tumor DNA (ctDNA) was extracted from the patient’s plasma (10 mL) at two time points (before treatment and at the first response evaluation or end of the treatment). The DNA NGS library and solution-based target enrichment were performed at IMBdx, Inc. (Seoul, Korea), using AlphaLiquid100. The captured DNA libraries were sequenced using the Illumina NovaSeq 6000 platform (Illumina, San Diego, CA) in the 2×150 bp paired-end mode.

Related Product

Circulating Tumor DNA Panel for 

Colorectal / Lung / Breast Cancer


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The circulating tumor DNA (ctDNA) was extracted from the patient’s plasma (10 mL) at two time points (before treatment and at the first response evaluation or end of the treatment). The DNA NGS library and solution-based target enrichment were performed at IMBdx, Inc. (Seoul, Korea), using AlphaLiquid100. The captured DNA libraries were sequenced using the Illumina NovaSeq 6000 platform (Illumina, San Diego, CA) in the 2×150 bp paired-end mode.


liquid-biopsy

Colorectal Cancer
Sensitivity Freq. 0.5% 100%
Freq. 1.0% 100%
Specificity 97.9%


liquid-biopsy

Breast Cancer
Sensitivity Freq. 0.5% 94.4%
Freq. 1.0% 100%
Specificity 96.3%


liquid-biopsy

Lung Cancer
Sensitivity Freq. 0.5% 100%
Freq. 1.0% 100%
Specificity 100%




Image_blog-Thumbnail_Celemics Contact Us_image_link_Got Questions

Discovery and Validation of Survival-Specific Genes in Papillary Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel

Cancers

Discovery and Validation of Survival-Specific Genes in Papillary Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel

Hwang J, Bang S, Choi MH, Hong SH, Kim SW, Lee HE, Yang JH, Park US, Choi YJ. Discovery and Validation of Survival-Specific Genes in Papillary Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel. Cancers. 2024 Jan;16(11):2006.

 

10.3390/cancers16112006


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Case report: Compound heterozygous variants detected by next-generation sequencing in a Tunisian child with ataxia-telangiectasia

Frontiers in Neurology

Case report: Compound heterozygous variants detected by next-generation sequencing in a Tunisian child with ataxia-telangiectasia

Ammous-Boukhris N, Abdelmaksoud-Dammak R, Ben Ayed-Guerfali D, Guidara S, Jallouli O, Kamoun H, Charfi Triki C, Mokdad-Gargouri R. Case report: Compound heterozygous variants detected by next-generation sequencing in a Tunisian child with ataxia-telangiectasia. Frontiers in Neurology. 2024 May 31;15:1344018.

 

10.3389/fneur.2024.1344018


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