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  • C12Q2600/00—Oligonucleotides characterized by their use
  • C12Q2600/158—Expression markers

Definitions

• the present invention relates to a process for personalization of cancer treatment involving the use of specific genes and/or their proteins in diagnostic tests for predicting prognosis, recurrence, resistance or sensitivity to therapy and metastasis status in cancer.
• cancer and its progression in an individual is guided by the expression and/or altered status of many genes and gene products (molecular markers). Correlation of the changes in these molecular markers can help to predict if a particular patients cancer would (a) recur in time after treatment or (b) be sensitive or resistant to therapies or (c) have metastasized at the time of initial discovery of the tumor, consequently leading to improved ability to manage cancer.
• Molecular signature refers to the expression of two or more genes described in Tables I- V, or more specifically Table X, in a tumor tissue or in tumor cells derived from tongue or other head-and-neck cancers; the said gene expression level being determined by one or more techniques that is commonly employed for measuring gene expression levels in tissues or cells which includes microarrays and real-time quantitative polymerase chain reaction. Levels of gene expression could also be determined by measuring the level of proteins encoded by the said genes using immunohistochemistry, enzyme-linked-immunosorbent assay or other methods like proteomic techniques for mapping expression of multiple proteins.
• Molecularly-targeted therapies shall mean a treatment modality against cancer cells targeting specific molecules involved in tumorigenesis and tumor growth.
• Immuno modulation therapy shall mean the use of modulators that inhibit/stimulate the immune system to elicit anti-tumor effects.
• tongue cancer is used as an example of head and neck cancer and other carcinomas to describe a method utilizing a set of genes or gene products whose altered expression, in head and neck tumor in general including tongue cancer, predicts (a) probability of recurrence in time after treatment (b) sensitivity or resistance to therapies or (c) probability of metastasis at the time of initial discovery of the tumor,
• the novel molecular signature comprises of a combination of genes selected from the list of genes given in Tables I-V or a narrower set of more differentially expressed genes from a preferred list of genes drawn from Tables I-V and listed in Table X.
• the molecular signature is identified in pre- treatment and post-treatment head and neck cancer and is used to determine the probability of recurrence of cancer after surgery and anti-cancer therapy. Absence of the molecular signature in the primary tumor sample would imply a far less probability of recurrence ; hence one could avoid further therapy after surgery, thus decreasing the cost of treatment as well as the morbidity associated with chemotherapy. Presence of the molecular signature in the tumor at the time of surgery would reveal a higher probability of recurrence and therefore would aid in determining if adjuvant chemotherapy is warranted or not.
• the molecular signature is used to identify sensitivity or resistance to anti-cancer agents, in particular chemotherapy agents, but not limited to the same, and would include radiation therapy or new generation molecularly- targeted drugs or immune-modulating drugs or cell therapy like dendritic cell therapy.
• the present invention also identifies a molecular signature, listed in Table V, which is differentially expressed in the adjacent histologically normal mucosa of the recurrent and non -recurrent patients.
• This molecular signature describes groups of cells in the adjacent mucosa of the recurrent patients that show the over expression of stem cell markers and transcription factors. The presence of these cells, as identified by the molecular signature, in the adjacent mucosa could also be predictive of recurrence in patients with head and neck cancer.
• the molecular signature is used to determine the probability that a tumor would has metastasized to a secondary location at the time of diagnosis of the disease, which will allow one to determine if surgery alone is sufficient or adjuvant chemotherapy or other anti-cancer drugs or therapies are required.
• the molecular signature in Table I-V, and more specifically Table X describes characteristics of the tumor that can be also used to predict if the cancer has metastasized to a secondary location by virtue of (a) the fact that the molecular signature identifies aggressive cells in the tumor that by definition has a higher invasive potential (b) the immune repressive genes that are over- expressed would allow the tumor to escape its primary site and metastasize.
• the non-recurrent set primarily showed Interferon signaling; Cytotoxic T- lymphocyte mediated apoptosis of target cells, protein ubiquitination and Myc mediated apoptosis as significant pathways.
• the tumor tissue that is used for analysis include tissue biopsies - either frozen, fixed in RNA stabilizing solutions or in paraffin-embedded- formalin fixed tissues (FFPE), or saliva which is used as the source RNA or protein for determination of the molecular signature
• the assays used for determining the molecular signature includes microarray, quantitative real-time PCR, immunohisotochemisitry, enzyme-linked immunosorbent assay, proteomic analysis or other standard methods of measuring gene expression of multiple directly or through proteins encoded by the genes.
• Table VII List of top 10 significant genes in Non-Recurrent/recurrent tongue cancer
• Fig 3 Significant pathways between Non-recurrent and recurrent tongue cancer Pathway analysis was carried out by Ingenuity Pathway Analysis (IP A) and the top 10 significant pathways are represented in the figure. The pathways are sorted according to significance in recurrent sub set (A) and non-recurrent samples (B).
• IP A Ingenuity Pathway Analysis
• FIG 4 Interaction networks identified by Ingenuity Pathway Analysis Interaction network of genes that are differentially expressed between Non-recurrent and recurrent tumors (A & B).
• A Activation
• E Expression
• PP protein- Protein Interaction
• I Inhibition
• L Proteolysis
• P Phosphorylation
• T Transcription
• PD Protein-DNA interaction.
• HBB and HBA1 The binding partners HBB and HBA1 are both higher in expression in non-recurrent tumors.
• Fig 5 Validation in tissues and saliva samples.
• the expression profile of a select subset of markers was validated in tongue cancer specimens (A).
• a distinct difference in expression profile of 4 genes (COL5A1, IGLA, HBB and CTSC) was observed in the primary tissue of patients that were non-recurrent (Group I) and recurrent (Group II).
• the pattern of expression obtained in the patients of the latter group was similar to that obtained in the recurrent tissue of patients (Group III).
• ROC analysis revealed these markers as most significant according to the AUC (B).
• the profile of 6 genes in saliva samples from normal (N) and tumor (T) samples is shown (C).
• the normal samples primarily show the expression of IL1B while at least one of the carcinogenesis related genes are expressed in the patients.
• ROC analysis of the combination of markers shows sensitivity of 0.65 and specificity of 0.87 (D).
• Fig 6 Irnmunohistochemical analysis of candidate markers IHC was carried out on tongue cancer samples (A) with antibodies to HBB (a, b, c, d) and COL5A1 (e, f, g, h). The expression was analyzed in normal controls (a, e), in non-recurrent tumor samples (b & f) and in recurrent samples (c & g). d & h represent negative controls.
• the non-recurrent tumor sample showed a high expression of HBB as observed in the normal control; while an over expression of COL5A1 was observed in the recurrent tumor sample.
• the magnifications (100 or 200 times the original magnification) are mentioned on each panel.
• ROC analysis showed HBB as a better candidate marker as compared to COL5A1 (B & C).
• the present invention describes a molecular signature comprising of a set of genes or gene products whose altered expression in head and neck tumor in general including tongue cancer predicts (a) resistance to chemotherapy, which would help avoid chemotherapy or use other modalities of treatment (c) probability of recurrence of the disease post treatment (d) determining probability of metastasis at the time of surgery thereby allowing one to determine if adjuvant therapy is required or not.
• Example 1 Patient details and sample collection
• tissue samples are collected from patients undergoing surgical treatment after obtaining mandatory approvals (Table VI).
• the samples that were subjected to microarray analysis were collected in RNA later (Ambion, Austin, USA), while the samples for validation were either snap frozen or collected in RNA later and archived at -80°C if required to be stored.
• the clinical characteristics of the patients are obtained from the electronic medical records maintained at the tertiary care cancer center.
• the sample sets were grouped into three categories: Group I (Pre-treatment, non-recurrent), which included pre-treatment tissues from patients who remained disease-free after standard treatment (surgery and adjuvant chemo radiation); Group II (Pre-treatment resistant/recurrent) included pre-treatment tissues from those who recurred during a 2-year follow up period; Group III (post-treatment recurrent; standard treatment) included recurrent tissue from patients with the recurrent disease. Group I & III were analyzed by micro array, while the validation was carried out in all the three groups. The adjacent mucosal tissue was collected 2 cm away from the tumor and confirmed as histologically negative for malignancy.
• Example 2 RNA isolation, labeling of cRNA and hybridization
• the preliminary analysis to ascertain the internal controls and the hybridization efficiency was carried out using the Gene Chip Operating Software (GCOS) and Microarray Suite (MAS5,Affymetrix, CA, USA).
• the CEL files were extracted and imported into GeneSpring 7.2 (Agilent Technologies, CA, USA) software package for analysis.
• Raw image data were background corrected, normalized and summarized into probe set expression values using Robust Microarray Analysis (RMA) algorithm.
• RMA Robust Microarray Analysis
• data from each chip was normalized to 50% of the measurements taken from that chip (measurements of ⁇ 0.01 were set to 0.01). Probe sets that were not reliably detected were removed, by filtering out those whose expression level was not >50 and confidence -values ⁇ 0.05, in at least 20% of the samples.
• Ingenuity Pathway Analysis was carried out to identify significant functions, signaling pathways and networks (Ingenuity Systems Inc. CA, USA) at the default core analysis and core comparison platforms. Fishers exact test was used to identify the statistically significant functions/pathways.
• the differentially expressed genes were hierarchically clustered using Multi Experiment Viewer, v 4.5 (MeV) (TM4 Microarray Software Suite, The Institute of Genomic Research (TIGR) with the Euclidean distance measurement and p values were calculated after application of the non-parametric Wilcoxon-Mann Whitney test (p ⁇ 0.5).
• Example 4 Validation of the microarray data in tissue and saliva samples by Quantitative PCR
• the expression levels of the genes selected for validation (MMP1, EMP1, ABCG1, COL5A1, IgLA, HBB, CTSC and CCL18) (Table I) was assessed by QRT PCR using the relative quantification ( ⁇ method). Expression was normalized using the endogenous control (GAPDH) and normal oral mucosal tissues were used as the calibrator. Melting curve analysis was done to ensure the specificity of the product obtained.
• GPDH endogenous control
• RT-PCR Reverse Transcription PCR
• a subset of 10 candidate markers (MMP1, FN1, FAPA, SERPINH2, IL8, IL1B, IgLA, ABCG1, COL5A1, HBB), were tested for their expression in saliva by QRT PCR as above. Saliva samples from healthy volunteers as the calibrator.
• the combined test result in the binary input format was used for the statistical analysis.
• the expression patterns were correlated to the disease status of the patients to ascertain their clinical relevance.
• the protein expression of two representative genes (COL5A1 and HBB), validated by QRT PCR was profiled in the tissue sections of a different cohort of patients with tongue cancer.
• the sections were deparaffinized and IHC carried out according to standard protocols.
• the antibodies were used in dilutions of 1:50 for both COL5A1 (scl33162; Santacruz Biotechnology, Santacruz, CA, USA) and HBB (H4890; Sigma Aldrich, USA).
• the sections were microwaved for antigen retrieval and the staining detected by Dako REALTM En Vision kit (Dako Corporation, Carpenteria, CA, USA).
• the sections were counterstained using haematoxylin and scanned at low and high power to identify areas of even staining and percentage of positive cells.
• the grades of positivity were scored as follows; negative ( ⁇ 1%), grade I (1-10%), grade II (10-30%), III (30-60%) and IV (>60%).
• the intensity of staining was also graded as mild, moderate and intense.
• the expression in the normal oral mucosal tissues was used as control.
• Receiver Operating Characteristic (ROC) curve analyses were carried out by SPSS 19 (IBM) and MedCalc® v 11.6.0.0 for the QPCR and IHC results. Area under the curve was computed via numerical integration of the ROC curves. The biomarkers, individually or in combination, with the largest Area under Curve (AUC) were identified to have the maximum predictive power for disease recurrence. Multiple regression analysis was also carried out by the stepwise method to identify the predictive value of the marker combinations.
• AUC Area under Curve
• Example 6 Determination of molecular signature from FFPE samples
• Formalin-fixed paraffin embedded (FFPE) samples of tumor and adjacent tissue is a convenient source for obtaining RNA for identification of the molecular signature described in this invention.
• 10 ⁇ curl sections is cut from FFPE blocks of cancer or adjacent tissue, placed in a 1.5 ml microcentrifuge tube and heated at 70°C in a heating block for 20 min to allow excess paraffin wax to be removed.
• Pre-warmed xylene (1 ml) is added to the tube and heated at 50°C for 10 min.
• the microfuge tube is then centrifuged at 12000g for 2 min in a microcentrifuge. Waste xylene is removed by pipette and the xylene wash repeated twice more. Residual xylene is removed by the addition of 1.0 ml of 100% ethanol to the dewaxed tissue sections, which will be allowed to stand for 10 min at room temperature.
• the tissue is centrifuged 12,000g for 5 min and the ethanol removed by pipette, and the process repeated once more with 100% ethanol.
• the tissue is rehydrated with 1.0 ml 90% ethanol for 5 min and finally washed in 1.0 ml 70% ethanol for 5 min.
• the sample is air dried to allow the ethanol to evaporate completely prior to protease digestion.
• Protease digestion is performed by use of a Recoverall kitTM (Applied Biosystems, AM 1975) as per the manufacturer's protocol following which 480 ⁇ 1 of the Ambion RecoverAllTM Isolation Additive is added to the microfuge tube, and vortex mixed for 20 seconds and allowed to stand for 15 min at room temperature.
• the tubes are pulse spun in a microfuge at 12000g for 30 seconds. Two 240 ⁇ aliquots of the resulting lysate is then stored at -20°C for RNA extraction.
• RNA extraction is performed using the Recoverall kitTM as per manufacturer's instructions. RNA is eluted finally in a volume of 60 ⁇ . Purity and quantity are checked spectrophotometry at 260 nm and 280 nm by placing 1.3 ⁇ of eluate on the sampling pedestal of a scanning spectrophotometer. Aliquots of each sample are stored at -80°C or reverse transcribed to produce cDNA in a two step RT-PCR reaction. RNA from fresh- frozen samples will be obtained using the RNeasy kit from Qiagen, according to the manufacturer's protocol.
• RNAs The amount and quality of RNAs is assessed by UV spectrophotometry and considered adequate for further analysis if the optical density 260/280 ratio is > 1.8 and the total RNA yield > 500ng.
• RNA-cDNA from FFPE tissues
• PCRs of a housekeeper gene e.g. PGK
• amplicons of increasing length from 50 to 200
• Quantitative Real Time PCR is carried out by the SYBR Green or Fluorescent dual labeled probe method on a real-time PCR machine, in this case- an ABI 7300 Cycler (Applied Biosystems, CA, USA).
• the expression levels of the genes selected from Table X are assessed by QRT PCR using either the relative quantification method (AACT method) [Livak and Schmittgen, Methods 25 (2001), 402-408] using normalizer genes such as GAPDH, which is used in the present study. Normal oral mucosal tissue or other standard RNA samples could be used as Calibrator, if required. Melting curve analysis is done to ensure the specificity of the product obtained, when using SYBR green method.
• Molecular signature can be identified by determining the expression of the individual genes represented in the signature or through determination of the proteins that these genes encode. While several methods can be used to determine the molecular signature identified in this invention, the following method is used to draw inferences from the molecular signature based on values in Table X as follows

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• 2012
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