WO2023004460A1 - Procédés de détection et/ou de diagnostic du cancer pancréatique - Google Patents

Procédés de détection et/ou de diagnostic du cancer pancréatique Download PDF

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WO2023004460A1
WO2023004460A1 PCT/AU2022/050794 AU2022050794W WO2023004460A1 WO 2023004460 A1 WO2023004460 A1 WO 2023004460A1 AU 2022050794 W AU2022050794 W AU 2022050794W WO 2023004460 A1 WO2023004460 A1 WO 2023004460A1
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seq
subject
level
expression
genes
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PCT/AU2022/050794
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Joanne Margaret LUNDY
Brendan John JENKINS
Daniel Gerald CROAGH
Hugh Yang GAO
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Hudson Institute of Medical Research
Monash University
Monash Health
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Priority claimed from AU2021902314A external-priority patent/AU2021902314A0/en
Application filed by Hudson Institute of Medical Research, Monash University, Monash Health filed Critical Hudson Institute of Medical Research
Publication of WO2023004460A1 publication Critical patent/WO2023004460A1/fr

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    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
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    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6844—Nucleic acid amplification reactions
    • C12Q1/6851—Quantitative amplification
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    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6869—Methods for sequencing
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    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/112—Disease subtyping, staging or classification
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
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    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/16—Primer sets for multiplex assays

Definitions

  • the present invention relates to methods of detecting and/or diagnosing pancreatic cancer in a subject.
  • the present invention also provides methods of resolving an inconclusive cytological assessment in a subject.
  • Pancreatic ductal adenocarcinoma is the 7 th leading cause of cancer related death worldwide. Most patients present with locally advanced or metastatic disease, with fewer than 20% presenting with lesions amenable to potentially curative surgery. The mainstay of treatment for patients with locally advanced and metastatic disease is chemotherapy, which may prolong survival for several months. However, despite incremental improvements in recent years the prognosis of PDAC remains dire, with a 5-year survival rate of just 9%.
  • PDAC neurodegenerative disease 2019
  • Many patients present with non-specific symptoms, and current imaging modalities and biomarkers such as carbohydrate antigen 19.9 (CA19.9) may not detect early stage disease or clearly differentiate PDAC from other causes of solid pancreatic masses, which may include other malignant conditions such as pancreatic neuroendocrine tumours (pNETs), lymphomas and metastases, as well as benign conditions such as autoimmune pancreatitis and pseudo-tumoural lesions.
  • Other factors contributing to poor outcomes in PDAC include the propensity for early distant metastasis, a complex tumour microenvironment characterized by dense stromal desmoplasia and immune dysregulation, and inherent resistance to standard treatments such as chemotherapy.
  • Endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) is considered the gold standard diagnostic method for the biopsy of suspicious pancreatic masses, and is a widely available procedure with low procedural morbidity and mortality.
  • a recent meta-analysis reported pooled sensitivity for the diagnosis of PDAC of 85%, with high specificity of 98% (Hewitt et al., 2012). However, approximately 15% of patients fail to achieve a tissue diagnosis with their first attempt at biopsy and may require further diagnostic procedures. EUS-FNA sensitivity has also been reported to be lower in the setting of chronic pancreatitis, an established risk factor for PDAC.
  • the present inventors have identified a gene expression signature associated with solid pancreatic cancer.
  • the inventors have identified a gene expression signature that provides a prompt and accurate clinical diagnosis of solid pancreatic cancer using EUS-FNA biopsy, where cellularity and tissue yield are highly variable between patients.
  • the gene expression signature provides diagnostic accuracy when a cytological assessment of cell morphology is inconclusive.
  • KRAS mutant allele detection further improves diagnostic accuracy, whilst also provides a novel surrogate marker of cellular adequacy in frozen EUS-FNA biopsies.
  • the present invention provides a method of detecting and/or diagnosing solid pancreatic cancer in a subject, the method comprising determining a level of expression of at least five or more or all of the genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SI OOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the subject.
  • the method comprises determining the level of expression of at least seven genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SI OOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the subject.
  • the method comprises determining the level of expression of at least ten genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SI OOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the subject.
  • the method comprises determining the level of expression of at least fifteen genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SI OOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the subject.
  • the method comprises determining the level of expression of all of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB 3, S100A2, COL17A1, MSLN, SIOOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the subject.
  • At least one or more of the genes is selected from the group consisting of LAMC2, IQGAP3, SIM2, PTK6, LAMB3, COL17A1, GJB4 and PADI1.
  • At least one gene is LAMC2.
  • At least one gene is IQGAP3.
  • At least one gene is SIM2.
  • At least one gene is PTK6.
  • At least one gene is LAMB3.
  • At least one gene is COL17A1.
  • At least one gene is GJB4.
  • At least one gene is PADI1
  • the method comprises: a) at least one or more of the genes selected from the group consisting of GJB3, b) at least one or more of the genes selected from the group consisting of LAMC2, IQGAP3, SIM2, PTK6, LAMB3, COL17A1, GJB4 and PADI1.
  • the method is performed on an endoscopic ultrasound fine needle aspiration (EUS-FNA) biopsy obtained from a subject.
  • EUS-FNA endoscopic ultrasound fine needle aspiration
  • the method further comprises performing genomic sequencing on the EUS-FNA biopsy if solid pancreatic cancer cells are present.
  • the method comprises normalizing the level of expression of the gene to a standard to obtain a normalized level of the gene.
  • the standard is one or more or all control genes selected from the group consisting of RPS11, RPL11, RPL28, RPSW, GDI2, RPL37A, PARK7, CNBP, CSNK1A1, RPS4X, MAZ, SF3B1, HSD17B4, DAP3, SET, MTIF3, Clorf43, CNOT2, GSTK1, DCTD, FNDC3B, AKIRIN1, ANXA7, SUPT5H, ZMYM2, DDX3X, HNRNPDL, ECD, MAEA, ADAR and ARCN1.
  • the one or more or all control genes comprise or consist of a sequence set forth in any one of SEQ ID NOs: 35 to 65.
  • the present disclosure also provides one or more control genes selected from the group consisting of RPS11, RPL11, RPL28, RPS16, GDI2, RPL37A, PARK7, CNBP, CSNK1A1, RPS4X, MAZ, SF3B1, HSD17B4, DAP3, SET, MTIF3, Clorf43, CNOT2, GSTK1, DCTD, FNDC3B, AKIRIN1, ANXA7, SUPT5H, ZMYM2, DDX3X, HNRNPDL, ECD, MAEA, ADAR and ARCN1.
  • the disclosure provides one or more control genes comprising or consisting of a sequence set forth in any one of SEQ ID NOs: 35 to 65.
  • the method comprises comparing the normalized level of expression of the gene in the subject to at least one reference level.
  • the reference value is a predetermined level of the gene and/or a predetermined score.
  • the method comprises a higher level of expression of the gene in the subject compared to the reference level is indicative of solid pancreatic cancer in the subject.
  • the methods as described herein can detect pancreatic cancer in a subject with a greater specificity and sensitivity (assessed by ROC analysis as area under the curve; AUC) than standard cytological analysis.
  • the area under the curve (AUC) of the gene is between about 0.70 and about 0.95.
  • the AUC of the gene is at least 0.70, or at least 0.70, or at least 0.75, or at least 0.85, or at least 0.90, or at least 0.95.
  • the method comprises determining the level of LAMC2 and the AUC is at least 0.90.
  • the AUC is 0.91.
  • the method comprises determining the level of TFAP2A and the AUC is at least 0.70.
  • the AUC is 0.74.
  • the method comprises determining the level of IQGAP3 and the AUC is at least 0.80.
  • the AUC is 0.84.
  • the method comprises determining the level of SIM2 and the AUC is at least 0.80.
  • the AUC is 0.80.
  • the method comprises determining the level of PTK6 and the AUC is at least 0.75.
  • the AUC is 0.79.
  • the method comprises determining the level of TMPRSS4 and the AUC is at least 0.90.
  • the AUC is 0.91.
  • the method comprises determining the level of SERPINB5 and the AUC is at least 0.85.
  • the AUC is 0.89.
  • the method comprises determining the level of LAMB3 and the AUC is at least 0.85.
  • the AUC is 0.86.
  • the method comprises determining the level of S100A2 and the AUC is at least 0.85.
  • the AUC is 0.86.
  • the method comprises determining the level of COL17A1 and the AUC is at least 0.80.
  • the AUC is 0.82.
  • the method comprises determining the level of MSLN and the AUC is at least 0.90.
  • the AUC is 0.94.
  • the method comprises determining the level of SIOOP and the AUC is at least 0.75.
  • the AUC is 0.79.
  • the method comprises determining the level of PLEKHN1 and the AUC is at least 0.75.
  • the AUC is 0.76.
  • the method comprises determining the level of GJB3 and the AUC is at least 0.85.
  • the AUC is 0.86.
  • the method comprises determining the level of GJB4 and the AUC is at least 0.85.
  • the AUC is 0.89.
  • the method comprises determining the level of PADI1 and the AUC is at least 0.75.
  • the AUC is 0.77.
  • the method comprises determining the level of CEACAM5 and the AUC is at least 0.85.
  • the AUC is 0.89.
  • the combined area under the curve (AUC) of the at least 5 or more or all genes is at least 0.85, or at least 0.90, or at least 0.95.
  • the combined AUC of the at least 5 or more or all genes is 0.90.
  • the combined AUC of the at least 5 or more or all genes is 0.97.
  • the methods as described herein can detect pancreatic cancer in a subject with greater accuracy than standard cytology analysis.
  • the method comprises diagnosing solid pancreatic cancer in a subject with at least 75% accuracy.
  • the accuracy is at least about 75%, at least about 80%, at least about 85%, at least about 90%, or at least about 95%.
  • the accuracy is about 75%.
  • the accuracy is about 80%.
  • the accuracy is about 90%.
  • the method comprises performing real-time reverse transcription polymerase chain reaction (RT-PCR), droplet digital PCR (ddPCR), RNA sequencing and/or a microarray assay.
  • RT-PCR real-time reverse transcription polymerase chain reaction
  • ddPCR droplet digital PCR
  • RNA sequencing and/or a microarray assay.
  • the method comprises performing RT-PCR.
  • the method comprises performing ddPCR.
  • the method comprises performing RNA sequencing.
  • the method comprises performing a microarray assay.
  • the level of expression is detected by using one or more probes or primers specific for each gene.
  • the level of expression is detected by using one, or two, or three, or four probes or primers specific for each gene.
  • the level of expression is detected by using one probe or primer specific for each gene.
  • the level of expression is detected by using two probes or primers specific for each gene.
  • the level of expression is detected by using three probes or primers specific for each gene.
  • the level of expression is detected by using four probes or primers specific for each gene.
  • the level of expression of the five or more or all genes and/or the level of expression of one or more or all control genes is detected by using one or more probes or primers specific for each gene.
  • the one or more probes or primers for the five or more or all genes bind to a sequence set forth in any one of SEQ ID NO: 18 to 34.
  • the one or more probes or primers bind to LAMC2.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 18.
  • the one or more probes or primers bind to TFAP2A.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 19.
  • the one or more probes or primers bind to IQGAP3.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 20.
  • the one or more probes or primers bind to SIM2.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 21.
  • the one or more probes or primers bind to PTK6.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 22.
  • the one or more probes or primers bind to TMPRSS4.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO:
  • the one or more probes or primers bind to SERPINB5.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO:
  • the one or more probes or primers bind to LAMB3.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 25.
  • the one or more probes or primers bind to S100A2.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 26.
  • the one or more probes or primers bind to COL17A1.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 27.
  • the one or more probes or primers bind to MSLN.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 28.
  • the one or more probes or primers bind to SI OOP.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 29.
  • the one or more probes or primers bind to PLEKHN1.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 30.
  • the one or more probes or primers bind to GJB3.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 31.
  • the one or more probes or primers bind to GJB4.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 32.
  • the one or more probes or primers bind to PADI1.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 33.
  • the one or more probes or primers bind to CEACAM5.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 34.
  • the one or more probes or primers for the one or more or all control genes bind to a sequence set forth in any one of SEQ ID NO: 66 to 96.
  • the one or more probes or primers bind to RPS11.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 66.
  • the one or more probes or primers bind to RPL11.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 67.
  • the one or more probes or primers bind to RPL28.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 68.
  • the one or more probes or primers bind to RPS16.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 69.
  • the one or more probes or primers bind to GD12.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 70.
  • the one or more probes or primers bind to RPL37A.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 71.
  • the one or more probes or primers bind to PARK7.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 72.
  • the one or more probes or primers bind to CNBP.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 73.
  • the one or more probes or primers bind to CSNK1A1.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 74.
  • the one or more probes or primers bind to RPS4X.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 75.
  • the one or more probes or primers bind to MAZ.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 76.
  • the one or more probes or primers bind to SF3B1.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 77.
  • the one or more probes or primers bind to HSD17B4.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 78.
  • the one or more probes or primers bind to DAP 3.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 79.
  • the one or more probes or primers bind to SET.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 80.
  • the one or more probes or primers bind to MTIF3.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 81.
  • the one or more probes or primers bind to Clorf43.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 82.
  • the one or more probes or primers bind to CNOT2.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 83.
  • the one or more probes or primers bind to GSTK1.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 84.
  • the one or more probes or primers bind to DCTD.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 85.
  • the one or more probes or primers bind to FNDC3B.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 86.
  • the one or more probes or primers bind to AKIRIN1.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 87.
  • the one or more probes or primers bind to ANXA7.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 88.
  • the one or more probes or primers bind to SUPT5H.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 89.
  • the one or more probes or primers bind to ZMYM2.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 90.
  • the one or more probes or primers bind to DDX3X.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 91.
  • the one or more probes or primers bind to HNRNPDL.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 92.
  • the one or more probes or primers bind to ECD.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 93.
  • the one or more probes or primers bind to MAEA.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 94.
  • the one or more probes or primers bind to ADAR.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 95.
  • the one or more probes or primers bind to ARCN1.
  • the one or more probes or primers bind to a sequence set forth in SEQ ID NO: 96.
  • the solid pancreatic cancer is selected from the group consisting of ductal adenocarcinoma, osteoclast-like giant cell tumour, acinar cell carcinoma, a neuroendocrine tumour and pancreatoblastoma.
  • the solid pancreatic cancer is ductal adenocarcinoma.
  • the solid pancreatic cancer is osteoclast-like giant cell tumour.
  • the solid pancreatic cancer is acinar cell carcinoma.
  • the solid pancreatic cancer is pancreatoblastoma.
  • the solid pancreatic cancer is a neuroendocrine tumour.
  • the method comprises detecting and/or diagnosing a solid pancreatic cancer from normal tissue.
  • the method comprises distinguishing or differentiating a solid pancreatic cancer from normal tissue.
  • the method comprises detecting and/or diagnosing a solid pancreatic cancer from pancreatitis.
  • the method comprises distinguishing or differentiating a solid pancreatic cancer from pancreatitis.
  • the pancreatitis is autoimmune pancreatitis.
  • the method comprises detecting and/or diagnosing a pancreatic ductal adenocarcinoma (PD AC) from a non- PD AC.
  • the method comprises distinguishing or differentiating a PDAC from a non-PDAC.
  • the non- PDAC is a pancreatic neuroendocrine tumour (pNET).
  • the method comprises distinguishing or differentiating a PDAC from a pNET.
  • the method further comprises determining the KRAS mutation status of the subject.
  • the KRAS mutation is a codon 12, 13 and/or 61 mutation.
  • the KRAS mutation is a codon 12 mutation.
  • the KRAS mutation is a G12D (c.35G>A), G12V (c.35G>T), G12R (c.35G>C), G12C (c.34G>T) and/or a G12A (c.35G>C) mutation.
  • the KRAS mutation is a G12D (c.35G>A) mutation.
  • the KRAS mutation is a G12V (c.35G>T) mutation.
  • the KRAS mutation is a G12R (c.35G>C) mutation.
  • the KRAS mutation is a G12A (c.35G>C) mutation.
  • the KRAS mutation is a G12C (c.34G>T) mutation.
  • the KRAS mutation is a codon 13 mutation.
  • the KRAS mutation is a G13C (c.37G>T) mutation.
  • the KRAS mutation is a codon 61 mutation.
  • the KRAS mutation is a Q61H (c. 183A>C), Q61R (C.182A>G), and/or Q61F (C.182A>T) mutation.
  • the KRAS mutation is a Q61H (c. 183A>C) mutation. In one example, the KRAS mutation is a Q61R (C.182A>G) mutation. In a further example, the KRAS mutation is a Q61F (C.182A>T) mutation.
  • determining the KRAS mutation status of the subject comprises determining the KRAS mutation allele fraction (MAF).
  • determining the KRAS MAF comprises determining the ratio of mutant KRAS and wild-type KRAS alleles at the mutation site.
  • the present invention also provides a method of resolving an inconclusive cytological assessment of clinically relevant cells in a sample obtained from a subject, the method comprising determining a level of expression of at least five or more or all of the genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SI OOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the sample, wherein the expression of at least five or more or all of the genes in the clinically relevant cells indicates the presence of malignant pancreatic cells.
  • the present invention further provides a method of determining whether a subject has solid pancreatic cancer when a cytological assessment of cell morphology is inconclusive for the cancer, the method comprising determining a level of expression of at least five or more or all of the genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SIOOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the sample, wherein the expression of at least five or more or all of the genes in the clinically relevant cells indicates that the subject has solid pancreatic cancer.
  • the present invention also provides a method of determining whether a subject has solid pancreatic cancer, the method comprising: i) performing a cytological assessment of cell morphology on a sample obtained from the subject to determine the morphology of one or more clinically relevant cells; and ii) determining a level of expression of at least five or more or all of the genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SI OOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the sample, wherein when the cytological assessment of cell morphology is inconclusive for the cancer, the expression of at least five or more or all of the genes in the clinically relevant cells indicates that the subject has solid pancreatic cancer.
  • the present invention further provides a method of treating solid pancreatic cancer in a subject, the method comprising detecting and/or diagnosing pancreatic cancer in the subject according to a method disclosed herein, and administering a treatment to the subject.
  • treatment comprises surgery, ablative or embolization therapy, chemotherapy, radiation therapy, targeted drug therapy, immunotherapy or a combination thereof.
  • the treatment comprises surgery.
  • the surgery is debulking surgery.
  • the treatment comprises ablative or embolization therapy.
  • the ablative therapy is selected from the group consisting of radio frequency ablation (RFA), microwave thermotherapy, ethanol (alcohol) ablation and cryosurgery.
  • the embolization therapy is selected from the group consisting of arterial embolization, chemoembolization and radioembolization.
  • the treatment comprises chemotherapy.
  • the chemotherapy is selected from the group consisting of gemcitabine, 5-fluoro uracil, oxaliplatin, albumin-bound paclitaxel, capecitabine, docetaxel, cisplatin, irinotecan.
  • the treatment comprises radiation therapy.
  • the radiation therapy is selected from the group consisting of external beam therapy (EBT), stereotactic body radiation (SBRT), or proton beam radiation therapy.
  • the treatment comprises targeted drug therapy.
  • the targeted drug therapy is selected from the group consisting of erlotinib (e.g., Tarceva®), olaparib (e.g., Lynparza®), larotrectinib (e.g., Vitrakvi®) and entrectinib (e.g., Rozlytrek®).
  • the treatment comprises immunotherapy.
  • the immunotherapy is pembrolizumab (e.g., Keytruda®).
  • the present invention also provides a kit or panel for detecting and/or diagnosing solid pancreatic cancer in an EUS-FNA biopsy obtained from a subject, the kit or panel comprising five or more probes or primers for detecting at least five or more of all of the genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SI OOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5.
  • the method further comprising one or more probes or primers for detecting one or more control genes selected from the group consisting of RPS11, RPL11, RPL28, RPS16, GDI2, RPL37A, PARK7, CNBP, CSNK1A1, RPS4X, MAZ, SF3B1, HSD17B4, DAP3, SET, MTIF3, Clorf43, CNOT2, GSTK1, DCTD, FNDC3B, AKIRIN1, ANXA7, SUPT5H, ZMYM2, DDX3X, HNRNPDL, ECD, MAEA, ADAR and ARCNL
  • composition of matter, group of steps or group of compositions of matter shall be taken to encompass one and a plurality (i.e. one or more) of those steps, compositions of matter, groups of steps or group of compositions of matter.
  • Figure 1 Retrospective review of diagnostic accuracy of EUS-FNA biopsies in VPCB cohort. Clinico-patho logical information was assessed for 416 consecutive biopsies stored in the VBCP between Jan 2016 and Dec 2019, to identify 308 pancreatic EUS-FNA biopsies meeting the criteria indicated. The final clinical and cytological diagnosis for these biopsies is indicated in the flow chart.
  • Figure 2. Selection of candidate genes from RNAseq cohort. Two-dimensional principle component analysis plot of gene expression of each sample in the VPCB RNA seq cohort (A). Genes fulfilling the abundance criteria were selected and ranked according to their ability to discriminate between PD AC and non- PD AC samples (B).
  • Discriminative performance of each gene was measured by calculating the area under the curve of a receiver operating characteristic curve and the top 20 genes were selected (C). The expression of the 20 genes were summarised into a single score for each sample using the ssGSEA method (D). Boxplot (E) and receiver operating characteristic plot (F) of the 20-gene signature demonstrate good discrimination between PD AC and non-PDAC samples in RNA-seq cohort.
  • FIG. 3 Validation of diagnostic gene signature in five external cohorts. Heat maps and ROC curves were generated to assess the 20-gene signature in five external cohorts containing PD AC and non-PDAC samples. AUC results under ROC curves demonstrate excellent discriminating power for the gene signature in E-MEXP-1121/E-MEXP-950, GSE101462, GSE15471, GSE28735 and GSE101448. Cohorts E-MEXP1121/ E- MEXP-950, GSE15471 and GSE28735 did not contain microarray probes for ENSG00000105388.
  • FIG. 4 Performance of 17-gene signature in validation cohort.
  • the performance of each of the genes in the 20-gene signature were calculated in the Nanostring validation cohort by constructing a receiver operating characteristic curve and measuring the area under the curve (A). Three poorly performing genes were removed from the signature, and the expression of the remaining 17 genes were summarised into a single gene score for each sample (B). Boxplot (C) and receiver operating characteristic curve (D) indicate that the gene score performs well at discriminating between PDAC and non-PDAC samples in the validation cohort.
  • SEQ ID NO: 1 is a nucleotide sequence of human LAMC2 SEQ ID NO: 2 is a nucleotide sequence of human TFAP2A SEQ ID NO: 3 is a nucleotide sequence of human IQGAP3 SEQ ID NO: 4 is a nucleotide sequence of human SIM2 SEQ ID NO: 5 is a nucleotide sequence of human PTK6 SEQ ID NO: 6 is a nucleotide sequence of human TMPRSS4 SEQ ID NO: 7 is a nucleotide sequence of human SERPINB5 SEQ ID NO: 8 is a nucleotide sequence of human LAMB3 SEQ ID NO: 9 is a nucleotide sequence of human S100A2 SEQ ID NO: 10 is a nucleotide sequence of human COL17A1 SEQ ID NO: 11 is a nucleotide sequence of human MSLN SEQ ID NO: 12 is a nucleotide sequence of human SIOOP SEQ ID NO
  • the term about refers to +/- 10%, more preferably +/- 5%, more preferably +/- 1%, of the designated value.
  • the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. That is, unless specified otherwise, or clear from context, “X employs A or B” is intended to mean any of the natural inclusive permutations. That is, if X employs A; X employs B; or X employs both A and B, then “X employs A or B” is satisfied under any of the foregoing instances. Further, at least one of A and B and/or the like generally means A or B or both A and B.
  • the articles “a” and “an” as used in this application and the appended claims may generally be construed to mean “one or more” unless specified otherwise or clear from context to be directed to a singular form.
  • nucleic acid refers to any nucleic acid
  • oligonucleotide refers to any nucleic acid molecules
  • polynucleotide refers to any combination of nucleic acid molecules.
  • Both terms are used to denote DNA, RNA, modified or synthetic DNA or RNA (including, but not limited to nucleic acids comprising synthetic and naturally-occurring base analogs, dideoxy or other sugars, thiols or other non-natural or natural polymer backbones), or other nucleobase containing polymers capable of hybridizing to DNA and/or RNA. Accordingly, the terms should not be construed to define or limit the length of the nucleic acids referred to and used herein, nor should the terms be used to limit the nature of the polymer backbone to which the nucleobases are attached.
  • nucleic acid sequence or “polynucleotide sequence” refers to a contiguous string of nucleotide bases and in particular contexts also refers to the particular placement of nucleotide bases in relation to each other as they appear in a polynucleotide.
  • the term “subject” shall be taken to mean any animal including humans, for example a mammal. Exemplary subjects include but are not limited to humans, non-human primates, canines and felines. For example, the subject is a human. In another example, the subject is a canine.
  • detecting refers to the identification of the presence or existence of solid pancreatic cancer in a subject at any stage of its development.
  • diagnosis refers to the identification of the specific disease or condition in the subject. For example, “diagnosis” occurs following the manifestation of symptoms but prior to a clinical diagnosis. In one example, “diagnosis” allows a confirmation of pancreatic cancer in a subject suspected of having pancreatic cancer.
  • solid pancreatic cancer refers to the presence of cells in the pancreas possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features known in the art.
  • the "solid pancreatic cancer” includes pre-malignant as well as malignant cancers.
  • the pancreatic cancer is a malignant cancer.
  • the solid pancreatic cancer is selected from the group consisting of ductal adenocarcinoma, osteoclast-like giant cell tumour, acinar cell carcinoma, a neuroendocrine tumour and pancreatoblastoma.
  • the solid pancreatic cancer is ductal adenocarcinoma.
  • the solid pancreatic cancer is osteoclast-like giant cell tumour.
  • the solid pancreatic cancer is acinar cell carcinoma.
  • the solid pancreatic cancer is pancreatoblastoma.
  • the solid pancreatic cancer is a neuroendocrine tumour.
  • the skilled person will understand that solid pancreatic cancer can be classified based on the grade of the cancer.
  • the solid pancreatic cancer is a grade I tumour.
  • the solid pancreatic cancer is a grade II tumour. In one example, the solid pancreatic cancer is a grade III tumour.
  • the solid pancreatic cancer is a grade IV tumour.
  • the methods of the present disclosure can be readily applied to any form of solid pancreatic cancer.
  • the present disclosure provides a method of detecting and/or diagnosing solid pancreatic cancer in a subject irrespective of the grade of the cancer.
  • the subject suffers from solid pancreatic cancer.
  • a subject suffering from solid pancreatic cancer has a clinically accepted diagnosis of solid pancreatic cancer.
  • the subject suffers from one or more symptoms of solid pancreatic cancer.
  • the method of the present disclosure is performed after the onset of one or more symptoms, i.e., the method is performed on a subject in need thereof.
  • the subject does not suffer from one or more symptoms of solid pancreatic cancer.
  • the method of the present disclosure is performed before the onset of one or more symptoms.
  • the subject is asymptomatic.
  • Symptoms of solid pancreatic cancer will be apparent to the skilled person and include, for example:
  • methods of the present disclosure may be combined with other diagnostic tests.
  • methods further comprise determining the KRAS mutation status of the subject.
  • methods of the disclosure further comprise performing a tumour biopsy.
  • the present disclosure provides a method of detecting and/or diagnosing solid pancreatic cancer in a subject, the method comprising determining a level of expression of at least five or more or all of the genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SIOOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the subject.
  • LAMC2 encodes a protein Laminin subunit gamma 2 which is part of the family of extracellular matrix glycoproteins, a major noncollagenous constituent of basement membranes.
  • LAMC2 as set forth in Ensembl Gene ID ENSG00000058085.
  • an exemplary sequence of human LAMC2 is set out in NCBI reference sequence NM_005562.2 and SEQ ID NO: 1.
  • An exemplary target sequence of LAMC2 is set forth in SEQ ID NO: 18.
  • TFAP2A encodes the Transcription Factor AP-2 Alpha protein which acts as a sequence- specific DNA-binding transcription factor recognising and binding to the specific DNA sequence and recruiting transcription machinery.
  • TFAP2A as set forth in Ensembl Gene ID ENSG00000137203.
  • an exemplary sequence of human TFAP2A is set out in NCBI reference sequence NM_003220.2 and SEQ ID NO: 2.
  • An exemplary target sequence of TFAP2A is set forth in SEQ ID NO: 19.
  • IQGAP3 encodes Ras GTPase-activating-lIke protein IQGAP3, also known as pl95, which is a ubiquitously expressed protein involved in regulating various cellular processes ranging from organization of the actin cytoskeleton, transcription, and cellular adhesion to regulating the cell cycle.
  • IQGAP3 as set forth in Ensembl Gene ID ENSG00000183856.
  • an exemplary sequence of human IQGAP3 is set out in NCBI reference sequence NM_178229.4 and SEQ ID NO: 3.
  • An exemplary target sequence of IQGAP3 is set forth in SEQ ID NO: 20.
  • SIM2 encodes the protein single-minded homolog 2 that plays a major role in the development of the central nervous system midline a well as the construction of the face and head.
  • SIM2 as set forth in Ensembl Gene ID ENSG00000159263.
  • an exemplary sequence of human SIM2 is set out in NCBI reference sequence NM_005069.3 and SEQ ID NO: 4.
  • An exemplary target sequence of SIM2 is set forth in SEQ ID NO: 21.
  • PTK6 encodes a cytoplasmic non-receptor protein kinase, tyrosine-protein kinase 6, which functions as an intracellular signal transduce in epithelial tissues.
  • the encoded protein has also been shown to undergo autophosphorylation.
  • PTK6 as set forth in Ensembl Gene ID ENSG00000101213.
  • an exemplary sequence of human PTK6 is set out in NCBI reference sequence NM_001256358.1 and SEQ ID NO: 5.
  • An exemplary target sequence of PTK6 is set forth in SEQ ID NO: 22.
  • TMPRSS4 encodes transmembrane protease serine 4 which is a member of the serine protease family known to be involved in a variety of biological processes.
  • the encoded protein is membrane bound with a N-terminal anchor sequence and a glycosylated extracellular region containing the serine protease domain.
  • TMPRSS4 as set forth in Ensembl Gene ID ENSG00000137648.
  • an exemplary sequence of human TMPRSS4 is set out in NCBI reference sequence NM_019894.3 and SEQ ID NO: 6.
  • An exemplary target sequence of TMPRSS4 is set forth in SEQ ID NO: 23.
  • SERPINB5 encodes the mammary serine protein inhibitor protein maspin.
  • Maspin is a non-inhibitory and obligate intracellular member of the serpin superfamily.
  • SERPINB5 as set forth in Ensembl Gene ID ENSG00000206075.
  • an exemplary sequence of human SERPINB5 is set out in NCBI reference sequence NM_002639.4 and SEQ ID NO: 7.
  • An exemplary target sequence of SERPINB5 is set forth in SEQ ID NO: 24.
  • LAMB 3 encodes the beta 3 subunit of laminin, a basement membrane protein.
  • LAMB3 as set forth in Ensembl Gene ID ENSG00000196878.
  • an exemplary sequence of human EAMB3 is set out in NCBI reference sequence NM_000228.2 and SEQ ID NO: 8.
  • An exemplary target sequence of LAMB3 is set forth in SEQ ID NO: 25.
  • S100A2 encodes the S100 calcium-binding protein A2 which is important in cyto skeletal organisation, whilst also playing a role in differentiation and regeneration of tissues.
  • S100A2 as set forth in Ensembl Gene ID ENSG00000196754.
  • an exemplary sequence of human S100A2 is set out in NCBI reference sequence NM_005978.3 and SEQ ID NO: 9.
  • An exemplary target sequence of S100A2 is set forth in SEQ ID NO: 26.
  • COL17A1 encodes the alpha chain of type XVII collagen.
  • Collagen XVII is a structural component of hemidesmosomes, multiprotein complexes at the dermal- epidermal basement membrane zone that mediate adhesion of keratinocytes to the underlying membrane.
  • COL17A1 as set forth in Ensembl Gene ID ENSG00000065618.
  • an exemplary sequence of human COL17A1 is set out in NCBI reference sequence NM_000494.3 and SEQ ID NO: 10.
  • An exemplary target sequence of COL17A1 is set forth in SEQ ID NO: 27.
  • MSLN encodes mesothelin a 40kDa protein that is expressed in mesothelial cells.
  • MSLN as set forth in Ensembl Gene ID ENSG00000102854.
  • an exemplary sequence of human MSLN is set out in NCBI reference sequence NM_013404.3 and SEQ ID NO: 11.
  • An exemplary target sequence of MSLN is set forth in SEQ ID NO: 28.
  • SIOOP encodes S100 calcium-binding protein P expressed in various normal tissues. S100P is involved in diverse biological functions but the exact role or mechanism of its action is still largely unknown.
  • SWOP as set forth in Ensembl Gene ID ENSG00000163993.
  • an exemplary sequence of human SWOP is set out in NCBI reference sequence NM_005980.2 and SEQ ID NO: 12.
  • An exemplary target sequence of SWOP is set forth in SEQ ID NO: 29.
  • PLEKHN1 encodes pleckstrin homology domain containing, family N member 1 which is involved in intracellular signaling or as a constituent of the cytoskeleton.
  • PLEKHN1 as set forth in Ensembl Gene ID ENSG00000187583.
  • an exemplary sequence of human PEEKHN1 is set out in NCBI reference sequence NM_032129.2 and SEQ ID NO: 13.
  • An exemplary target sequence of PLEKHN1 is set forth in SEQ ID NO: 30.
  • GJB3 encodes the protein Gap junction beta-3, also known as connexin 31.
  • the encoded protein is a component of gap junctions, which are composed of arrays of intercellular channels that provide a route for the diffusion of low molecular weight materials from cell to cell.
  • GJB3 as set forth in Ensembl Gene ID ENSG00000188910.
  • an exemplary sequence of human GJB3 is set out in NCBI reference sequence NM_001005752.1 and SEQ ID NO: 14.
  • An exemplary target sequence of GJB3 is set forth in SEQ ID NO: 31.
  • GJB4 encodes the protein Gap junction beta-4 protein (GJB4), also known as connexin 30.3 (Cx30.3). Connexin 30.3 is part of the group of proteins that form gap junctions on the surface of cells and is also thought to play a role in the growth and maturation of epidermal cells.
  • GJB4 as set forth in Ensembl Gene ID ENSG00000189433.
  • an exemplary sequence of human GJB4 is set out in NCBI reference sequence NM_153212.1 and SEQ ID NO: 15.
  • An exemplary target sequence of GJB4 is set forth in SEQ ID NO: 32.
  • PADI1 encodes the protein Peptidyl arginine deiminase, type I Peptidyl arginine deiminase, type I, which is a member of the peptidyl arginine deiminase family of enzymes which catalyze the post-translational deimination of proteins by converting arginine residues into citrullines in the presence of calcium ions.
  • PADI1 as set forth in Ensembl Gene ID ENSG00000142623.
  • an exemplary sequence of human PADI1 is set out in NCBI reference sequence NM_013358.2 and SEQ ID NO: 16.
  • An exemplary target sequence of PADI1 is set forth in SEQ ID NO: 33.
  • CEACAM5 encodes the cell surface glycoprotein carcinoembryonic antigen- related cell adhesion molecule 5. The encoded protein is thought to play a role in regulating differentiation, apoptosis and cell polarity.
  • CEACAM5 as set forth in Ensembl Gene ID ENSG00000105388.
  • an exemplary sequence of human CEACAM5 is set out in NCBI reference sequence NM_004363.2 and SEQ ID NO: 17.
  • An exemplary target sequence of CEACAM5 is set forth in SEQ ID NO: 34.
  • the methods of any disclosure described herein comprise determining a level of expression of at least five or more or all of the genes recited in the previous 17 paragraphs.
  • the genes of the present disclosure includes genes with partly modified and/or substituted nucleotides.
  • the genes include all transcripts and/or variants of the genes disclosed herein. Accordingly, in any of the methods as described herein, the genes do not have 100% sequence identity with the sequences (e.g., the target sequence) of the genes as listed above.
  • the measured gene has at least 75%, or at least 80%, or at least 85%, or at least 90%, or at least 95%, or at least 97.5%, or at least 98%, or at least 99%, or at least 99.9% sequence identity to the target gene sequence recited above.
  • the gene sequence has one, two, three or four nucleotide substitutions.
  • level or “level of expression” in reference to a gene shall be understood to refer to a measure of the gene transcript or number of copies of the gene.
  • methods of the present disclosure involve extracting or isolating DNA or RNA fractions from the biological sample. In another example, the methods involve isolating only the RNA fraction from the biological sample. In a further example, the methods involve isolating only the DNA fraction from the biological sample. In one example, the methods involve extracting cell-free DNA or RNA from the biological sample. For example, the methods involve isolating cell-free DNA from the biological sample. In another example, the methods involve isolating cell-free RNA from the biological sample.
  • Methods for the extraction of DNA or RNA fractions from the biological samples will be apparent to the skilled person and/or are described herein and include, for example, phenol-based techniques, combined phenol and column-based techniques.
  • a commercial kit may be used for RNA and/or DNA extraction including for example, isolation with the AllPrep DNA/RNA Universal Kit (Qiagen).
  • the quality and/or quantity of the extracted RNA and/or DNA may also be determined by any method known to a person skilled in the art e.g. spectrophotometrically at 260, 280 and 230 nm, agarose gel electrophoreses, or Bioanalyzer analysis (Agilent).
  • quantity of DNA and RNA may be assessed using the Nanodrop spectrophotometer (ThermoScientific) and Qubit Fluorometer (Life Technologies).
  • quality of DNA and RNA may be assessed using Bioanalyser and TapeStation systems (Agilent).
  • the level of expression of the gene may be normalized.
  • RNA transcript refers to the level of the RNA transcript, relative to the mean levels of a set or control set of reference RNA transcripts.
  • the reference RNA transcripts are based on their minimal variation across patients, tissues, or treatments.
  • the RNA transcript may be normalized to the totality of tested RNA transcripts, or a subset of such tested RNA transcripts.
  • the methods described herein comprises normalizing the level of expression of the gene to a standard to obtain a normalized level of the gene.
  • the standard is an endogenous control.
  • the endogenous control is a gene that shows minimal variation across patients, tissues, or treatments.
  • the endogenous control gene is a housekeeping gene.
  • the endogenous control is one or more genes selected from the group consisting of RPS11, RPL11, RPL28, RPS16, GDI2, RPL37A, PARK 7, CNBP, CSNK1A1, RPS4X, MAZ, SF3B1, HSD17B4, DAP3, SET, MTIF3, Clorf43, CNOT2, GSTK1, DCTD, FNDC3B, AKIRIN1, ANXA7, SUPT5H, ZMYM2, DDX3X, HNRNPDL, ECD, MAEA, ADAR and ARCNL
  • the endogenous control is ribosomal protein Sll ( RPS11 ).
  • RPS11 as set forth in Ensembl Gene ID ENSG00000142534.
  • an exemplary sequence of human RPS11 is set out in NCBI reference sequence NM_001015.3 and SEQ ID NO: 35.
  • An exemplary target sequence of RPS11 is set forth in SEQ ID NO: 66.
  • the endogenous control is ribosomal protein Lll ( RPL11 ).
  • RPL11 as set forth in Ensembl Gene ID ENSG00000142676.
  • an exemplary sequence of human RPL11 is set out in NCBI reference sequence NM_000975.2 and SEQ ID NO: 36.
  • An exemplary target sequence of RPL11 is set forth in SEQ ID NO: 67.
  • the endogenous control is ribosomal protein L28 ( RPL28 ).
  • RPL28 as set forth in Ensembl Gene ID ENSG00000108107.
  • an exemplary sequence of human RPL28 is set out in NCBI reference sequence NM_000991.3 and SEQ ID NO: 37.
  • An exemplary target sequence of RPL28 is set forth in SEQ ID NO: 68.
  • the endogenous control is ribosomal protein S16 ( RPS16 ).
  • RPS16 as set forth in Ensembl Gene ID ENSG00000105193.
  • an exemplary sequence of human RPS16 is set out in NCBI reference sequence NM_001020.4 and SEQ ID NO: 38.
  • An exemplary target sequence of RPS16 is set forth in SEQ ID NO: 69.
  • the endogenous control is GDP dissociation inhibitor 2 (GDI2 ).
  • GDI2 as set forth in Ensembl Gene ID ENSG00000057608.
  • an exemplary sequence of human GDI2 is set out in NCBI reference sequence NM_001494.3 and SEQ ID NO: 39.
  • An exemplary target sequence of CDI2 is set forth in SEQ ID NO: 70.
  • the endogenous control is ribosomal protein L37a ( RPL37A ).
  • RPL37A as set forth in Ensembl Gene ID ENSG00000197756.
  • an exemplary sequence of human RPL37A is set out in NCBI reference sequence NM_000998.4 and SEQ ID NO: 40.
  • An exemplary target sequence of RPL37A is set forth in SEQ ID NO: 71.
  • the endogenous control is Parkinsonism associated deglycase ( PARK7 ).
  • PARK7 as set forth in Ensembl Gene ID ENSG00000116288.
  • an exemplary sequence of human PARK7 is set out in NCBI reference sequence NM_001123377.1 and SEQ ID NO: 41.
  • An exemplary target sequence of PARK7 is set forth in SEQ ID NO: 72.
  • the endogenous control is CCHC-type zinc finger nucleic acid binding protein (CNBP ).
  • CNBP as set forth in Ensembl Gene ID ENSG00000169714.
  • an exemplary sequence of human CNBP is set out in NCBI reference sequence NM_003418.4 and SEQ ID NO: 42.
  • An exemplary target sequence of CNBP is set forth in SEQ ID NO: 73.
  • the endogenous control is casein kinase 1 alpha 1 ( CSNK1A1 ).
  • CSNK1A1 as set forth in Ensembl Gene ID ENSG00000113712.
  • an exemplary sequence of human CSNK1A1 is set out in NCBI reference sequence NM_001892.4 and SEQ ID NO: 43.
  • An exemplary target sequence of CSNK1A1 is set forth in SEQ ID NO: 74.
  • the endogenous control is ribosomal protein S4 X-linked ( RPS4X ).
  • RPS4X as set forth in Ensembl Gene ID ENSG00000198034.
  • an exemplary sequence of human RPS4X is set out in NCBI reference sequence NM_001007.4 and SEQ ID NO: 44.
  • An exemplary target sequence of RPS4X is set forth in SEQ ID NO: 75.
  • the endogenous control is MYC associated zinc finger protein ⁇ MAZ).
  • MAZ as set forth in Ensembl Gene ID ENSG00000103495.
  • an exemplary sequence of human MAZ is set out in NCBI reference sequence NM_002383.2 and SEQ ID NO: 45.
  • An exemplary target sequence of MAZ is set forth in SEQ ID NO: 76.
  • the endogenous control is splicing factor 3b subunit 1 ( SF3B1 ).
  • SF3B1 as set forth in Ensembl Gene ID ENSG00000115524.
  • an exemplary sequence of human SF3B1 is set out in NCBI reference sequence NM_001005526.1 and SEQ ID NO: 46.
  • An exemplary target sequence of SF3B1 is set forth in SEQ ID NO: 77.
  • the endogenous control is hydroxysteroid 17-beta dehydrogenase 4 (HSD17B4).
  • HSD17B4 as set forth in Ensembl Gene ID ENSG00000133835.
  • an exemplary sequence of human HSD17B4 is set out in NCBI reference sequence NM_000414.2 and SEQ ID NO: 47.
  • An exemplary target sequence of FISD17B4 is set forth in SEQ ID NO: 78.
  • the endogenous control is death associated protein 3 ( DAP3 ).
  • DAP3 as set forth in Ensembl Gene ID ENSG00000132676.
  • an exemplary sequence of human DAP3 is set out in NCBI reference sequence NM_004632.3 and SEQ ID NO: 48.
  • An exemplary target sequence of DAP 3 is set forth in SEQ ID NO: 79.
  • the endogenous control is SET nuclear proto-oncogene (SET).
  • SET nuclear proto-oncogene
  • SET as set forth in Ensembl Gene ID ENSG00000119335.
  • an exemplary sequence of human SET is set out in NCBI reference sequence NM_001122821.1 and SEQ ID NO: 49.
  • An exemplary target sequence of SET is set forth in SEQ ID NO: 80.
  • the endogenous control is mitochondrial translational initiation factor 3 (MTIF3 ).
  • MTIF3 as set forth in Ensembl Gene ID ENSG00000122033.
  • an exemplary sequence of human MTIF3 is set out in NCBI reference sequence NM_152912.3 and SEQ ID NO: 50.
  • An exemplary target sequence of MTIF3 is set forth in SEQ ID NO: 81.
  • the endogenous control is chromosome 1 open reading frame 43 ( Clorf43 ).
  • Clorf43 as set forth in Ensembl Gene ID ENSG00000143612.
  • an exemplary sequence of human Clorf43 is set out in NCBI reference sequence NM_015449.2 and SEQ ID NO: 51.
  • An exemplary target sequence of Clorf43 is set forth in SEQ ID NO: 82.
  • the endogenous control is CCR4-NOT transcription complex subunit 2 ( CNOT2 ).
  • CNOT2 as set forth in Ensembl Gene ID ENSG00000111596.
  • an exemplary sequence of human CNOT2 is set out in NCBI reference sequence NM_015449.2 and SEQ ID NO: 52.
  • An exemplary target sequence of CNOT2 is set forth in SEQ ID NO: 83.
  • the endogenous control is glutathione S-transferase kappa 1 ( GSTK1 ).
  • GSTK1 as set forth in Ensembl Gene ID ENSG00000197448.
  • an exemplary sequence of human GSTK1 is set out in NCBI reference sequence NM_015917.2 and SEQ ID NO: 53.
  • An exemplary target sequence of GSTK1 is set forth in SEQ ID NO: 84.
  • the endogenous control is dCMP deaminase (DCTD).
  • DCTD as set forth in Ensembl Gene ID ENSG00000129187.
  • an exemplary sequence of human DCTD is set out in NCBI reference sequence NM_001012732.1 and SEQ ID NO: 54.
  • An exemplary target sequence of DCTD is set forth in SEQ ID NO: 85.
  • the endogenous control is fibronectin type III domain containing 3B ( FNDC3B ).
  • FNDC3B as set forth in Ensembl Gene ID ENSG00000075420.
  • an exemplary sequence of human FNDC3B is set out in NCBI reference sequence NM_022763.3 and SEQ ID NO: 55.
  • An exemplary target sequence of FNDC3B is set forth in SEQ ID NO: 86.
  • the endogenous control is akirin 1 (AKIRIN1 ).
  • AKIRIN1 as set forth in Ensembl Gene ID ENSG00000174574.
  • an exemplary sequence of human AKIRIN1 is set out in NCBI reference sequence NM_001136275.1 and SEQ ID NO: 56.
  • An exemplary target sequence of AKIRIN1 is set forth in SEQ ID NO: 87.
  • the endogenous control is annexin A7 ( ANXA7 ).
  • ANXA7 as set forth in Ensembl Gene ID ENSG00000138279.
  • an exemplary sequence of human ANXA7 is set out in NCBI reference sequence NM_001156.3 and SEQ ID NO: 57.
  • An exemplary target sequence of ANXA7 is set forth in SEQ ID NO: 88.
  • the endogenous control is SPT5 homolog, DSIF elongation factor subunit ( SUPT5FT ).
  • SUPT5FI as set forth in Ensembl Gene ID ENSG00000196235.
  • an exemplary sequence of human SUPT5H is set out in NCBI reference sequence NM_003169.3 and SEQ ID NO: 58.
  • An exemplary target sequence of SUPT5FI is set forth in SEQ ID NO: 89.
  • the endogenous control is zinc finger MYM-type containing 2 ( ZMYM2 ).
  • ZMYM2 as set forth in Ensembl Gene ID ENSG00000121741.
  • an exemplary sequence of human ZMYM2 is set out in NCBI reference sequence NM_003169.3 and SEQ ID NO:
  • ZMYM2 is set forth in SEQ ID NO: 90.
  • the endogenous control is DEAD-box helicase 3 X-linked ( DDX3X ).
  • DDX3X as set forth in Ensembl Gene ID ENSG00000215301.
  • an exemplary sequence of human DDX3X is set out in NCBI reference sequence NM_001356.3 and SEQ ID NO:
  • An exemplary target sequence of DDX3X is set forth in SEQ ID NO: 91.
  • the endogenous control is heterogeneous nuclear ribonucleoprotein D like (. HNRNPDL ).
  • HNRNPDL as set forth in Ensembl Gene ID ENSG00000152795.
  • an exemplary sequence of human HNRNPDL is set out in NCBI reference sequence NR_003249.1 and SEQ ID NO: 61.
  • An exemplary target sequence of HNRNPDL is set forth in SEQ ID NO: 92.
  • the endogenous control is ecdysoneless cell cycle regulator ( ECD ).
  • ECD ecdysoneless cell cycle regulator
  • ECD as set forth in Ensembl Gene ID ENSG00000122882.
  • an exemplary sequence of human ECD is set out in NCBI reference sequence NM_001135752.1 and SEQ ID NO: 62.
  • An exemplary target sequence of ECD is set forth in SEQ ID NO: 93.
  • the endogenous control is macrophage erythroblast attacher, E3 ubiquitin ligase ( MAEA ).
  • MAE A as set forth in Ensembl Gene ID ENSG00000090316.
  • an exemplary sequence of human MAEA is set out in NCBI reference sequence NM_001017405.2 and SEQ ID NO: 63.
  • An exemplary target sequence of MAEA is set forth in SEQ ID NO: 94.
  • the endogenous control is adenosine deaminase RNA specific ( ADAR ).
  • ADAR as set forth in Ensembl Gene ID ENSG00000160710.
  • an exemplary sequence of human ADAR is set out in NCBI reference sequence NM_001111.3 and SEQ ID NO: 64.
  • An exemplary target sequence of ADAR is set forth in SEQ ID NO: 95.
  • the endogenous control is archain 1 ( ARCN1 ).
  • ARCN1 as set forth in Ensembl Gene ID ENSG00000095139.
  • an exemplary sequence of human ARCN1 is set out in NCBI reference sequence NM_001655.4 and SEQ ID NO: 65.
  • An exemplary target sequence of ARCN1 is set forth in SEQ ID NO: 96.
  • control genes of the present disclosure includes genes with partly modified and/or substituted nucleotides.
  • the genes include all transcripts and/or variants of the genes disclosed herein. Accordingly, in any of the methods as described herein, the genes do not have 100% sequence identity with the sequences (e.g., the target sequence) of the genes as listed above.
  • the measured gene has at least 75%, or at least 80%, or at least 85%, or at least 90%, or at least 95%, or at least 97.5%, or at least 98%, or at least 99%, or at least 99.9% sequence identity to the target gene sequence recited above.
  • the gene sequence has one, two, three or four nucleotide substitutions.
  • control is an exogenous control, for example an exogenous RNA added to the biological sample before RNA extraction (e.g., a spike-in control).
  • an exogenous RNA added to the biological sample before RNA extraction e.g., a spike-in control
  • Spike-in controls may be added to a sample before RNA is recovered, the amount of the spike-in control recovered after RNA is directly correlated with the amount of total RNA recovered.
  • the exogenous RNA is isolated from a host source or is synthetic.
  • normalizing the level of the gene is global mean normalisation.
  • global mean normalization refers to normalization of expression of a gene to a set of reference genes.
  • the method may comprise measuring the expression of at least three endogenous control genes and taking the geometric mean to provide a normalization factor.
  • the at least three endogenous control genes are expressed in all samples being analysed.
  • the method comprises comparing the level of expression of the RNA in the subject to a level of expression of the RNA in at least one reference.
  • Suitable reference samples for use in the methods of the present disclosure will be apparent to the skilled person and/or described herein.
  • the reference may be an internal reference (i.e., from the same subject), from a normal individual or an established data set (e.g., matched by age, gender, ethnicity, sample type and/or stage of disease).
  • the reference is an internal reference or sample.
  • the reference is an autologous reference.
  • the internal reference is obtained from the subject at an earlier time point as the sample under analysis.
  • normal individual shall be taken to mean that the subject is selected on the basis that they do not have a solid pancreatic cancer (e.g., healthy control) or other malignant and/or benign condition, or that they are not suspected of having such condition.
  • a solid pancreatic cancer e.g., healthy control
  • other malignant and/or benign condition e.g., benign cancer
  • the reference is an established data set.
  • Established data sets suitable for use in the present disclosure will be apparent to the skilled person and include, for example:
  • the method comprises determining:
  • a higher level of expression of the gene in the subject compared to the reference level is indicative of solid pancreatic cancer in the subject.
  • RNA nucleic acid molecules or copies of RNA in the subject is greater, increased or up-regulated, compared to a control or reference level. It will be apparent from the foregoing that the level of expression of the gene needs only be increased by a statistically significant amount, for example, by at least about 10%, or about 20%, or about 30%, or about 40%, or about 50%, or about 60%, or about 70%, or about 80%, or about 90%, or about 95%.
  • RNA nucleic acid molecules or copies of RNA in the subject is reduced, decreased or down-regulated, compared to a control or reference level. It will be apparent from the foregoing that the level of expression of the gene need only be decreased by a statistically significant amount, for example, by at least about 10%, or about 20%, or about 30%, or about 40%, or about 50%, or about 60%, or about 70%, or about 80%, or about 90%, or about 95%.
  • RNA nucleic acid molecules or copies of RNA in the subject is within about +/- 5% of the control or reference level.
  • the reference level is a predetermined threshold level of the gene assessed. In one example, the reference level is a standard curve of the gene assessed. In one example, there is a reference level for each of the genes assessed. Thus, in some examples of the present disclosure, the reference level may comprise a predetermined threshold or standard curve of one, two, three, four, five, six, seven or more genes.
  • the method, kit or panel described herein comprises a reference level for the gene LAMC2. In one example, the method, kit or panel described herein comprises a reference level for the gene TFAP2A. In one example, the method, kit or panel described herein comprises a reference level for the gene IQGAP3.
  • the method, kit or panel described herein comprises a reference level for the gene SIM2. In one example, the method, kit or panel described herein comprises a reference level for the gene PTK6. In one example, the method, kit or panel described herein comprises a reference level for the gene TMPRSS4. In one example, the method, kit or panel described herein comprises a reference level for the gene SERPINB5. In one example, the method, kit or panel described herein comprises a reference level for the gene LAMB3. In one example, the method, kit or panel described herein comprises a reference level for the gene S100A2. In one example, the method, kit or panel described herein comprises a reference level for the gene COL17A1.
  • the method, kit or panel described herein comprises a reference level for the gene MSLN. In one example, the method, kit or panel described herein comprises a reference level for the gene SIOOP. In one example, the method, kit or panel described herein comprises a reference level for the gene PLEKHN1. In one example, the method, kit or panel described herein comprises a reference level for the gene GJB3. In one example, the method, kit or panel described herein comprises a reference level for the gene GJB4. In one example, the method, kit or panel described herein comprises a reference level for the gene PADI1. In one example, the method, kit or panel described herein comprises a reference level for the gene CEACAM5.
  • a reference is not included in an assay. Instead, a suitable reference is derived from an established data set previously generated. Data derived from processing, analyzing and/or assaying a test sample is then compared to data obtained for the sample.
  • level of gene expression can be detected with any method known to a person skilled in the art including, for example, the methods described or adapted from Git et al. (2010), Hunt et al. (2015), Tackett et al. (2017) and Hu et al. (2017).
  • next generation sequencing single-molecule real-time sequencing, mass spect
  • Detection may include methods comprising direct labelling of a RNA (e.g. with a modified nucleotide, labelled nucleotide or tag incorporated into the RNA) or binding of the RNA with a binding molecule which binds a RNA or a truncated version thereof forming a RNA-binding molecule complex.
  • a RNA e.g. with a modified nucleotide, labelled nucleotide or tag incorporated into the RNA
  • binding of the RNA with a binding molecule which binds a RNA or a truncated version thereof forming a RNA-binding molecule complex.
  • the binding molecule is selected from: i) a polynucleotide, ii) an aptamer, iii) an antibody.
  • the polynucleotide is complementary to the RNA or a truncated version thereof or detects a tag attached to the RNA.
  • the polynucleotide is a primer.
  • the binding molecule is detectably labelled or capable of binding a detectable label.
  • the binding molecule is linked to an enzyme, enzyme substrate, a fluorescent or fluorescent substrate, chemiluminescent molecule, chemiluminescent substrate, purification tag and/or a solid support.
  • the mRNA-binding complex is directly or indirectly detected.
  • the methods as described herein can detect and/or diagnose solid pancreatic cancer in a subject with high specificity and sensitivity.
  • the sensitivity achieved by the presently claimed method for determining whether a subject has cancer is at least about at least about 60%, at least about 70%, at least about 71%, at least about 72%, at least about 73%, at least about 74%, at least about 75%, at least about 76%, at least about 77%, at least about 78%, at least about 79%, at least about 80%, at least about 81%, at least about 82%, at least about 83%, at least about 84%, at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%.
  • the sensitivity achieved by the presently claimed method for determining whether a subject has cancer is between about 65% and 90%.
  • the sensitivity is about 69%.
  • the sensitivity is about 80%.
  • the sensitivity is about 86%.
  • the specificity achieved by the presently claimed method for determining whether a subject has cancer is at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, or about 100%. In one example, the specificity achieved by the presently claimed method for determining whether a subject has cancer is 100%.
  • the specificity and sensitivity is assessed by receiver operative characteristic (ROC) analysis as area under the curve (AUC).
  • ROC receiver operative characteristic
  • the AUC of the level of the at least five genes detected is between about 0.8 and about 1.0. In one example, the AUC of the level of the at least five genes detected is between about 0.80 and about 0.90, for example at least 0.80, or at least 0.85, or at least 0.90. In another example, the AUC of the level of the at least one miRNA detected is between about 0.90 and about 1.0, for example at least 0.90, or at least 0.95, or 1.0. In one example, the AUC of the level of the at least five genes detected is 0.90. In another example, the AUC of the level of the at least five genes detected is 0.95. In another example, the AUC of the level of the at least five genes detected is 1.0.
  • the AUC of the level of each gene detected is at least 0.80, or at least 0.85, or at least 0.90, or at least 0.95, or at least 0.96, or at least 0.97, or at least 0.98, or at least 0.98.
  • the method comprises detecting the level of expression of at least five or more or all of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SI OOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 and the combined AUC is between about 0.8 and about 1.0.
  • the combined AUC of the at least five or more or all genes is 0.90.
  • the method comprises detecting the level of expression of all of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB 3, S100A2, COL17A1, MSLN, SIOOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 and the combined AUC is at least 0.90.
  • KRAS mutant allele detection further improves diagnostic accuracy of the method described herein, whilst also provides a novel surrogate marker of cellular adequacy in frozen EUS-FNA biopsies.
  • the method comprises determining the KRAS mutation status of the subject.
  • KRAS mutation status is determined using a commercially available kit (e.g., KRAS XL StripAssayTM; ViennaLab Diagnostics GmBH).
  • the KRAS mutation is a codon 12, 13 and/or 61 mutation.
  • the KRAS mutation is a codon 12 mutation.
  • the KRAS mutation is a G12D (c.35G>A), G12V (c.35G>T), G12R (c.35G>C), G12C (c.34G>T) and/or a G12A (c.35G>C) mutation.
  • the KRAS mutation is a G12D (c.35G>A) mutation. In another example, the KRAS mutation is a G12V (c.35G>T) mutation. In a further example, the KRAS mutation is a G12R (c.35G>C) mutation. In another example, the KRAS mutation is a G12A (c.35G>C) mutation. In another example, the KRAS mutation is a G12C (c.34G>T) mutation. In another example, the KRAS mutation is a codon 13 mutation. For example, the KRAS mutation is a G13C (c.37G>T) mutation. In a further example, the KRAS mutation is a codon 61 mutation.
  • the KRAS mutation is a Q61H (c. 183A>C), Q61R (C.182A>G), and/or Q61L(c.l82A>T) mutation.
  • the KRAS mutation is a Q61H (c. 183A>C) mutation.
  • the KRAS mutation is a Q61R (c.l82A>G) mutation.
  • the KRAS mutation is a Q61L (C.182A>T) mutation.
  • further determining the KRAS mutation status increases the accuracy of the method described herein by at least about 10%.
  • the accuracy of the method described herein increases by 10%, or by 12%, or by 14%, or by 16%, or by 18%, or by 18%, or by 20%.
  • further determining the KRAS mutation status increases the accuracy of the method described herein to at least 90% accuracy.
  • the accuracy is increased to about 90% accuracy, or about 91% accuracy, or about 92% accuracy, or about 93% accuracy, or about 94% accuracy, or about 95% accuracy, or about 96% accuracy, or about 97% accuracy.
  • determining the KRAS mutation status of the subject comprises determining the KRAS mutation allele fraction (MAF).
  • determining the KRAS MAF comprises determining the ratio of mutant KRAS and wild-type KRAS alleles at the mutation site.
  • KRAS MAF is determined using ddPCR.
  • the KRAS MAF is >1% as measured by ddPCR. It will be apparent to the skilled person from the disclosure herein that a MAF of >1% as measured by ddPCR is a good marker of cellular adequacy in EUS-FNA biopsy samples.
  • the cellular adequacy of an EUS-FNA biopsy samples is determined by determining the KRAS MAF.
  • the present disclosure also provides a method of resolving an inconclusive cytological assessment of clinically relevant cells in a sample.
  • the present disclosure also provides a method of determining whether a subject has solid pancreatic cancer when a cytological assessment of cell morphology is inconclusive for the cancer.
  • Cytological assessment involves the assessment of individual cells. "Cytological assessment" of cell morphology seeks to identify malignant cells based on morphologic characteristics. Cytological assessment of cell morphology is a procedure that is part of the standard of care and used alongside, or as a reflex to, further investigation for the detection of recurrence or the diagnosis of cancer. It is not a test per se but a pathology consultation based on a particular sample or sample set. The assessment procedure is complex and requires expertise and care in sample collection to provide a correct assessment.
  • a cell sample In performing a cytological assessment of cell morphology, a cell sample is typically fixed to a slide and viewed under a microscope to visually assess the morphology and cellular features. Before, visually assessing the slide, the sample may be stained to assist in visualising morphological changes to cells and cellular components. These stains can include a haematoxylin and eosin stain or Papanicolaou stain (Pap stain). Morphological changes that may be associated with cancer include enlarged nuclei with irregular size and shape, prominent nucleoli, scarce cytoplasm which may be intense or pale in colour.
  • clinically relevant cells refers to those cells that the cytologist or cytopathologist is examining to determine the cancer status of the patient.
  • the clinically relevant cells are epithelial cells from the pancreas. Excluded cells are considered not clinically relevant to determining whether a subject has cancer. The excluded cells will depend on the cancer being detected. More specifically, the skilled person will be aware of cell types in a sample related to a particular cancer.
  • excluded cells include, but are not necessarily limited to, one or more or all of T-cells, B-cells, neutrophils, macrophages, granulocytes, dendritic cells, mast cells, memory-cells, plasma cells, eosinophils and squamous cells.
  • T-cells T-cells
  • B-cells neutrophils
  • macrophages macrophages
  • granulocytes dendritic cells
  • mast cells granulocytes
  • memory-cells granulocytes
  • plasma cells eosinophils and squamous cells.
  • cytology assessment can often be inconclusive and not achieve its intended goal to aid in the diagnosis of cancer. Further, given the low sensitivity of cytology assessment, a negative or inconclusive cytology result does not preclude the presence of cancer (especially low grade cancer).
  • an inconclusive cytological assessment of cell morphology refers to an assessment that does not allow the presence of cancer to be determined. Often a cytological assessment of cell morphology is inconclusive as the assessment identifies cells that have lost their normal appearance but have not reached the level of abnormality of malignant cells. These cells are commonly referred to in the art as atypical cells in light of their atypical morphology.
  • the type and size of the biological sample will depend upon the detection means used.
  • sample refers to any type of suitable material obtained from the subject.
  • the term encompasses a clinical sample or biological fluid (e.g., biopsy or aspirated fluid, whole blood, serum, plasma, cerebrospinal fluid (CSF) sample, urine and saliva), tissue sample, live cells and also includes cells in culture, cell supernatants, cell lysates derived therefrom.
  • the sample can be used as obtained directly from the source or following at least one-step of (partial) purification. It will be apparent to the skilled person that the sample can be prepared in any medium which does not interfere with the method of the disclosure.
  • the sample may comprise cells or tissues and/or is an aqueous solution or biological fluid comprising cells or tissues.
  • the sample may also be a cell-free preparation.
  • the sample may be a cell-free aqueous solution or biological fluid, such as biopsy fluid following removal of the cells.
  • Pre-treatment may involve, for example, diluting viscous fluids.
  • Treatment of a sample may involve filtration, distillation, separation, concentration.
  • the biological sample is an endoscopic ultrasound fine needle aspiration (EUS-FNA) biopsy sample.
  • the EUS-FNA biopsy is a formalin- fixed, paraffin embedded (FFPE) biopsy, a snap frozen biopsy or a fresh biopsy.
  • the EUS-FINA biopsy is a FFPE biopsy.
  • the EUS-FNA biopsy is a snap frozen EUS-FNA biopsy sample.
  • the EUS-FNA biopsy is a fresh biopsy sample.
  • the EUS-FNA biopsy is a cell-free fluid biopsy sample.
  • the EUS-FNA biopsy is an aspirated cell-free fluid sample. It will be apparent to the skilled person that the aspirated cell-free fluid is the supernatant that is suspended above a cell pellet that is normally discarded and contains cell-free RNA.
  • the biological sample has been derived previously from the subject. Accordingly, in one example, a method as described herein according to any embodiment additionally comprises providing the biological sample.
  • a method as described herein according to any embodiment is performed using an extract from a sample, such as, for example, nucleic acids.
  • the present invention provides a method of treating solid pancreatic in a subject, the method comprising performing the method as described herein and treating the subject for pancreatic cancer.
  • the terms “treating”, “treat” or “treatment” includes surgically removing all or part of the cancer or administering a therapeutically effective amount of a compound/molecule/radiation sufficient to reduce or eliminate at least one symptom of the pancreatic cancer.
  • an "effective amount” for therapeutic uses is the amount of the compound required to provide a clinically significant decrease in disease symptoms without undue adverse side effects.
  • An appropriate "effective amount” in any individual case may be determined using techniques, such as a dose escalation study.
  • An "effective amount” of a compound is an amount effective to achieve a desired pharmacologic effect or therapeutic improvement without undue adverse side effects.
  • an effective amount or “a therapeutically effective amount” can vary from subject to subject, due to variation in metabolism of the compound of any of age, weight, general condition of the subject, the condition being treated, the severity of the condition being treated, and the judgment of the prescribing physician.
  • treatment comprises surgery, ablative or embolization therapy, chemotherapy, radiation therapy, targeted drug therapy, immunotherapy or a combination thereof.
  • the treatment comprises surgery.
  • the surgery is debulking surgery.
  • the treatment comprises ablative or embolization therapy.
  • the ablative therapy is selected from the group consisting of radio frequency ablation (RFA), microwave thermotherapy, ethanol (alcohol) ablation and cryosurgery.
  • the embolization therapy is selected from the group consisting of arterial embolization, chemoembolization and radioembolization.
  • the treatment comprises chemotherapy.
  • the chemotherapy is selected from the group consisting of gemcitabine, 5-fluoro uracil, oxaliplatin, albumin-bound paclitaxel, capecitabine, docetaxel, cisplatin, irinotecan.
  • the treatment comprises radiation therapy.
  • the radiation therapy is selected from the group consisting of external beam therapy (EBT), stereotactic body radiation (SBRT), or proton beam radiation therapy.
  • the treatment comprises targeted drug therapy.
  • the targeted drug therapy is selected from the group consisting of erlotinib (e.g., Tarceva®), olaparib (e.g., Lynparza®), larotrectinib (e.g., Vitrakvi®) and entrectinib (e.g., Rozlytrek®).
  • the treatment comprises immunotherapy.
  • the immunotherapy is pembrolizumab (e.g., Keytruda®).
  • kits for detecting and/or diagnosing cancer in a subject will preferably comprise a nucleotide array comprising RNA-specific probes and/or oligonucleotides for amplifying at least five or more or all of the genes described herein.
  • the present invention also provides a panel or kit comprising one or more reagents for detecting at least five or more or all of the genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SIOOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5.
  • the kit comprises reagents for detecting at least seven genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, SW0A2, COL17A1, MSLN, SWOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5.
  • the kit comprises reagents for detecting at least ten genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, SW0A2, COL17A1, MSLN, SWOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5 in the subject.
  • the kit comprises reagents for detecting at least fifteen genes selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, SW0A2, COL17A1, MSLN, SWOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5.
  • the kit comprises reagents for detecting all of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, SW0A2, COL17A1, MSLN, SWOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5.
  • the kit comprises reagents for detecting at least one or more of the genes is selected from the group consisting of LAMC2, IQGAP3, SIM2, PTK6, LAMB3, COL17A1, GJB4 and PADI1.
  • the panel or kit further comprises a control as described herein.
  • the panel or kit further comprises one or more reagents for detecting the level of a control.
  • the panel or kit comprises a reference level.
  • the reference level comprises a standard curve of the at least five or more or all genes as selected from the group consisting of LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SI OOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5.
  • the reference level comprises a predetermined threshold of the at least five or more or all genes selected from the group consisting LAMC2, TFAP2A, IQGAP3, SIM2, PTK6, TMPRSS4, SERPINB5, LAMB3, S100A2, COL17A1, MSLN, SIOOP, PLEKHN1, GJB3, GJB4, PADI1 and CEACAM5.
  • the panel or kit as described herein is for next generation sequencing, real-time reverse transcription polymerase chain reaction (RT-PCR), droplet digital PCR (ddPCR), RNA sequencing and/or a microarray assay.
  • RT-PCR real-time reverse transcription polymerase chain reaction
  • ddPCR droplet digital PCR
  • RNA sequencing RNA sequencing and/or a microarray assay.
  • the panel or kit as described herein is for ex vivo analysis.
  • the kit is suitable for use with tissue biopsy samples, for example EUS-FNA biopsy samples.
  • the panel or kit as described herein is suitable for high-throughput screening.
  • high-throughput screening refers to screening methods that can be used to test or assess more than one sample at a time and that can reduce the time for testing multiple samples.
  • the methods are suitable for testing or assessing at least 5 samples, at least 10, at least 20, at least 30, at least 50, at least 70, at least 90, at least 150, at least 200, at least 300 samples at a time.
  • Such high-throughput screening methods can analyse more than one sample rapidly e.g.
  • High-throughput screening may also involve the use of liquid handling devices.
  • high-throughput analysis may be automated.
  • Example 1 Materials and Methods Clinical samples and data
  • Pancreatic tissue samples were sourced from the Georgia Pancreatic Cancer Biobank (VPCB, HREC/15/MonH/117), which currently stores biospecimens from seven major tertiary centres in Victoria, Australia.
  • VPCB Victorian Pancreatic Cancer Biobank
  • EUS-FNA biopsies patients consented to an additional needle pass at the time of their standard of care biopsy, which is snap frozen and stored in the VPCB.
  • Relevant clinical data was extracted by retrospective review of medical records, and stored in a de-identified manner.
  • Tests for diagnostic accuracy were assessed by constructing 2 x 2 contingency tables using GraphPad Prism v8.0, with true positive cytology defined as those with confirmed malignancy or suspicious cytology. Cytology reported as “scant atypical cells” but no definite diagnosis, “indeterminate”, and “non-diagnostic” were considered false negative results for patients with PD AC. Fisher’s exact test was used to calculate P values and statistical significance, and Wilson-Brown method was used to calculate 95% confidence intervals. For descriptive statistics of the yield of RNA and DNA, data presented is the mean+SEM.
  • RNA and DNA were simultaneously extracted from snap-frozen pancreatic biopsies following the manufacturer’s protocol (Qiagen AllPrep DNA/RNA Universal Kit). Quantity of gDNA and RNA was assessed using the Nanodrop spectrophotometer (ThermoScientific) and Qubit Fluorometer (Life Technologies), and quality assessed using Bio analysesr and TapeStation systems (Agilent). KRAS testing was performed on gDNA using the KRAS XL StripAssay (ViennaLab Diagnostics GmBH).
  • RNA 50ng
  • Hybridization Buffer and Reporter CodeSet 50ng
  • Samples were immediately made up to 35pL using RNAse free water, loaded into nCounter Sprint Cartridges and run using the SPRINT profiler (Nanostring).
  • Gene expression normalisation was performed by dividing the expression of each signature gene by the geometric mean of the 30 housekeeping genes for each sample. Gene expression values were then z-transformed. To calculate the summarised gene expression score for each sample, z-transformed gene expression values were summarised into a single value for each sample using simple addition.
  • KRAS mutations in PDAC tissues were verified in duplicate by digital droplet PCR (ddPCR) with the inclusion of positive, negative and no-template controls, following manufacturer protocols ( KRAS G12/G13 or Q61H Screening Kit, Bio-Rad).
  • Droplets (15000-20000 per well) generated using the Q200X droplet generator were transferred to a 96- well PCR plate, heat- sealed, and subjected to thermocycling in a C1000 touch thermal cycler (Bio-Rad) under the following cycling conditions: 95°C for 10 min, 40 cycles at 94°C for 30 s and subsequently 55°C for 1 min, then followed by an enzyme deactivation step through incubation for 10 min at 98°C.
  • Amplified droplets were detected using a QX200 droplet reader (Bio-Rad Laboratories, Hercules, CA, USA) with two fluorescent detectors (FAM and HEX.
  • the determination of the number of mutation copies, ratio and fractional abundance (FA) of the samples was adjusted by the Quanta- Soft software (Bio-Rad Laboratories, Hercules, CA, USA) to fit a Poisson distribution model with a 95% confidence level. A minimum of three positive droplets across the two wells was required for a positive result for detection of rare events.
  • the ratio was calculated as the number of copies per microliter of mutant allele, divided by copies per microliter of wild-type allele.
  • the fractional abundance of mutant allele was measures by dividing the number of copies per microliter of mutant allele by the total copies per microliter of wild-type allele plus mutant allele.
  • Cytology confirmed a diagnosis of PD AC in 137 biopsies, and was suspicious or highly suspicious in a further 29. 11 biopsies were reported as atypical without definite evidence of malignancy, and 42 were either non-diagnostic or inadequate. There was one false positive result for PDAC, with initial cytology reported as adenocarcinoma, but at later review including clinical history and extensive immunohistochemical staining, the diagnosis was changed to pNET.
  • DNA and RNA was simultaneously extracted from an EUS-FNA biopsy and KRAS mutation testing performed.
  • RNA DNA 2427+289.4ng.
  • the mean RIN was 3.4+0.15, while the quality of DNA was generally higher, with a mean DIN of 7.1+0.13.
  • the KRAS XL StripAssayTM (ViennaLab Diagnostics GmBH) was selected as a commercially validated, relatively cost-effective method of testing with quick turn around time, which can detect mutations in specimens comprising 1-5% mutation positive cells.
  • KRAS mutation analysis was available for 174 PDAC samples and 23 benign tissues, and had diagnostic sensitivity for PDAC of 86.8% (95% Cl 80.1 to 91.0%), and specificity of 95.7% (95% Cl 79.0 to 99.8%) (Figure IB).
  • the single positive result in a benign biopsy was an equivocal KRAS G12V mutation, present at the very lower limit of detection of the assay.
  • a pancreatico-duodenectomy confirmed no invasive malignancy but focal areas of low grade pancreatic intraepithelial neoplasia (PanIN-lB), malignant pre-cursor lesions of which 10%-30% may harbour pathogenic KRAS mutations.
  • RNA sequencing differentiates PD AC from non-PDAC
  • Table 1 Clinicopathological features and demographics of patient cohort used for gene signature development. _
  • the control EUS- FNA biopsies were selected to include causes of suspicious pancreatic inflammation or solid masses on imaging which would generally warrant an urgent biopsy to exclude malignancy.
  • EUS-FNA PDAC biopsies provided a feasible source of genetic material for molecular analysis, and displayed a distinct gene expression profile when compared to non- PD AC controls.
  • 2 patients initially diagnosed with pancreatitis (with benign cytology and no clinical diagnosis of malignancy) were found to have outlying gene expression profiles in our test set, clustering with PDAC samples (Figure 2A).
  • Pathologic KRAS G12D mutations were detected in both apparently benign biopsies.
  • the diagnostic signature was applied to 5 publicly available cohorts of patients containing both PDAC and non-malignant controls (either benign specimens or microdissected adjacent normal tissue): E-MEXP-1121/E-MEXP-950, GSE101462, GSE15471, GSE28735 and GSE101448. Heat maps and ROC curves were generated to assess the diagnostic performance of the gene signature in each cohort (Figure 3). The predictive AUC in the respective external validation cohorts was 82%, 98%, 89%, 94% and 96%.
  • the selected genes were then used to create a custom NanoString CodeSet for testing in an independent patient cohort.
  • the NanoString system utilises a simple workflow which accommodates input of relatively low RNA quality and quantity (25ng) and allows complementary capture and reporter probes for all mRNA targets of interest to be mixed with RNA in a single hybridization reaction with no need for library preparation, with subsequent digital counting of colour-tagged codes for each mRNA target. Results are available within 24 hours, an attractive feature if applied in the clinical setting as data could be used in real time alongside standard cytology to aid in the interpretation of biopsy results.
  • the diagnostic gene signature was tested in an independent local cohort of a further 60 EUS-FNA patient biopsies.
  • the validation cohort consisted of 24 patients with cytologically confirmed PDAC, 20 patients with indeterminate or non-diagnostic cytology, 10 patients with clinically and cyto-logically benign pancreatic disease, and six patients with cytologically confirmed pNETs (Table 2).
  • TNM stage of PDAC patients [number (%)]
  • one of the patients with a final clinical diagnosis of pNET was initially erroneously diagnosed with adenocarcinoma on cytological assessment.
  • the diagnostic gene signature profile for this sample scored lowly, consistent with other pNETs, and lower than the PD AC biopsies.
  • the final clinical diagnoses consisted of two further pNETs, one benign pancreatitis, and a further 17 PDACs.
  • the mean RIN was 4.8 (range 2.3-8.7) in the validation cohort.
  • Table 3 Sensitivity, specificity, and accuracy of cytology, KRAS and NanoString signature in 60 validation samples.
  • KRAS KRAS mutation allele fraction
  • MAF mutant ATCkS'/wild type KRAS
  • ddPCR analysis was performed on a representative set of 32 specimens where adequate tumour-derived DNA was available ( Figure 5A).
  • MAF varied across the population but closely correlated with higher RNA signature expression ( Figure 5B-C), suggesting higher tumour cellularity in these samples and providing a rational explanation for lower signature expression in the outlier PDAC samples.
  • Cyto logically non-diagnostic specimens with negative KRAS, low signature expression and low MAF could therefore be presumed to be samples with very low (or no) tumour cells and would represent the population who would require further diagnostic biopsies.
  • 5 samples were identified which failed to meet the minimum requirement of either definitive cytology, positive KRAS (by StripAssay testing or MAF >1%), or a signature score above the defined PDAC cutoff. Therefore, these samples (8.3%) would represent the patient cohort who are likely to require a further diagnostic biopsy, a significantly lower proportion than we observed in our retrospective review of real-world patients.

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Abstract

La présente invention concerne des procédés de détection et/ou de diagnostic du cancer pancréatique chez un sujet. La présente invention concerne également des procédés de résolution d'une évaluation cytologique non concluante de cellules cliniquement pertinentes dans un échantillon prélevé sur un sujet.
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Citations (3)

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WO2004074510A1 (fr) * 2003-02-18 2004-09-02 Garvan Institute Of Medical Research Methodes pour le diagnostic et le prognostic du cancer du pancreas
WO2006024283A2 (fr) * 2004-08-31 2006-03-09 Technische Universität Dresden Composes et procedes pour traiter, diagnostiquer et pronostiquer des maladies pancreatiques
WO2016049276A1 (fr) * 2014-09-25 2016-03-31 Moffitt Genetics Corporation Biomarqueurs de tumeurs pronostiques

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WO2004074510A1 (fr) * 2003-02-18 2004-09-02 Garvan Institute Of Medical Research Methodes pour le diagnostic et le prognostic du cancer du pancreas
WO2006024283A2 (fr) * 2004-08-31 2006-03-09 Technische Universität Dresden Composes et procedes pour traiter, diagnostiquer et pronostiquer des maladies pancreatiques
WO2016049276A1 (fr) * 2014-09-25 2016-03-31 Moffitt Genetics Corporation Biomarqueurs de tumeurs pronostiques

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ALMEIDA PALLOMA PORTO, CARDOSO CRISTINA PADRE, DE FREITAS LEANDRO MARTINS: "PDAC-ANN: an artificial neural network to predict pancreatic ductal adenocarcinoma based on gene expression", BMC CANCER, vol. 20, no. 1, 1 December 2020 (2020-12-01), XP093030190, DOI: 10.1186/s12885-020-6533-0 *
ANONYMOUS: "[HG-U133_Plus_2 ] Affymetrix Human Genome U133 Plus 2.0 Array", NCBI, 14 June 2017 (2017-06-14), XP055381695, Retrieved from the Internet <URL:https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL570> [retrieved on 20170614] *
WILLIAM BERRY; ELIZABETH ALGAR; BEENA KUMAR; CHRISTOPHER DESMOND; MICHAEL SWAN; BRENDAN J. JENKINS; DANIEL CROAGH: "Endoscopic ultrasound‐guided fine‐needle aspirate‐derived preclinical pancreatic cancer models reveal panitumumab sensitivity in KRAS wild‐type tumors", INTERNATIONAL JOURNAL OF CANCER, JOHN WILEY & SONS, INC., US, vol. 140, no. 10, 28 February 2017 (2017-02-28), US , pages 2331 - 2343, XP071289761, ISSN: 0020-7136, DOI: 10.1002/ijc.30648 *
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