WO2014033245A1

WO2014033245A1 - Methods for predicting the outcome of a cancer in a patient by analysing snorna

Info

Publication number: WO2014033245A1
Application number: PCT/EP2013/067967
Authority: WO
Inventors: Pierre BROUSSET; Wilfried VALLERON; Laure BERQUET
Original assignee: INSERM (Institut National de la Santé et de la Recherche Médicale); Université Paul Sabatier Toulouse Iii
Priority date: 2012-08-31
Filing date: 2013-08-30
Publication date: 2014-03-06

Abstract

The present invention relates to a method for predicting the survival time of a patient suffering from a non-anaplastic PTCL comprising the steps consisting of i) measuring, in a sample obtained from the patient, the expression level of the snoRNA HBII-239 or the level expression of the has-mi R-768, ii) comparing said expression level with a predetermined reference value and iii) providing a good prognosis when the expression level of the snoRNA HBII-239 or the has-miR-768 is higher than the predetermined reference value and a poor prognosis when the expression level of the snoRNA HBII-239 or the has-mi R-768 is lower than the predetermined reference value.

Description

METHODS FOR PREDICTING THE OUTCOME OF A CANCER IN A PATIENT

BY ANALYSING SNORNA

FIELD OF THE INVENTION:

The present invention relates to a method for predicting the survival time of a patient suffering from a non-anaplastic PTCL comprising the steps consisting of i) measuring, in a sample obtained from the patient, the expression level of the snoRNA HBII-239 or the level expression of the has-miR-768, ii) comparing said expression level with a predetermined reference value and iii) providing a good prognosis when the expression level of the snoRNA HBII-239 or the has-miR-768 is higher than the predetermined reference value and a poor prognosis when the expression level of the snoRNA HBII-239 or the has-miR-768 is lower than the predetermined reference value.

BACKGROUND OF THE INVENTION:

Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of non-Hodgkin's lymphoma. The 2008 WHO classification recognizes peripheral T-cell lymphoma not otherwise specified (PTCL-NOS), angio-immunoblastic T-cell lymphoma (AITL) and anaplastic large cell lymphoma (ALCL; with or without anaplastic lymphoma kinase gene rearrangement, ALCL ALK+ or ALK-) as the most common tumors within the PTCL group [Sabattini E et al, 2010]. Several gene expression profiles were produced based on coding gene analysis providing some interesting help in term of diagnosis [Iqbal J, et al, 2010]. However, some difficulties remain to accurately classify some PTCL subtypes (ALK-ALCL vs. PTCL-NOS CD30+ and AITL vs. PTCL-NOS with expression of follicular helper T-cell markers). Still difficulties remain in obtaining reliable biological tools that can predict the clinical behavior of the PTCLs particularly after CHOP therapy (the most accepted frontline treatment). Prognostication with various scores are available: international prognostic index (IPI), IPI for PTCL (PIT), modified PIT (mPIT), and international PTCL project score (IPTCLP), all with a major caveat in distinguishing poor and very poor prognosis patients, making them somehow meaningless [Swerdlow SH CE et al, 2008]. Indeed, only 20% of PTCL patients have potential cure with the CHOP regimen, among which 50% have low IPI score [Vose J et al, 2008]. Overall, up to now patients diagnosed with PTCL receive a rather grim prognosis.

Recently, a molecular signature has been published that refines the classification of PTCL and helps to decipher some of the molecular pathways at play in subsets 2. These gene expression profiles have also afforded prognostic markers, but only for AITL in which a cell of origin was proposed (follicular helper T-cell) 2. In-depth analysis of PTCL has brought to light new potential therapeutic targets. Several clinical studies are ongoing, with moderate activity so far as single agent. The challenging issue with genetic signatures seems to be the prognostication and distinction between PTCL-NOS and ALK- ALCL [Kerry J. et al, 2011] In oncology, a large body of data is available for micro RNA expression patterns whereas the other classes of small non-coding RNAs have drawn less attention. Among these, the 60-300 nucleotides small nucleolar RNAs (snoRNAs) participate in diverse biological processes, most importantly ribosomal RNA maturation (by classic snoRNAs) [Hammann WNaC, 2005 and Bachellerie JP et al, 2002]. Despite this, the function of many snoRNAs, referred to as orphan snoRNAs, remains unknown. Mostly produced by disbranching from a spliced lariat of ribosomal or housekeeping gene introns, snoRNA expression has long been thought to be invariant Nevertheless, recent reports have shed light on new molecular functions of snoRNAs, or have demonstrated new expression patterns that could be associated with pathological features [Dong XY, et al, 2009].

SUMMARY OF THE INVENTION:

Using high-throughput quantitative PCR methods, the inventors demonstrate that snoRNA and micro RNA expression analysis is helpful in the context of PTCL, both in terms of diagnosis and prognostication in patients treated by conventional chemotherapy.

Thus, the invention relates to a method for predicting the survival time of a patient suffering from a non-anaplastic PTCL comprising the steps consisting of i) measuring, in a sample obtained from the patient, the expression level of the snoRNA HBII-239 or the level expression of the has-miR-768, ii) comparing said expression level with a predetermined reference value and iii) providing a good prognosis when the expression level of the snoRNA HBII-239 or the has-miR-768 is higher than the predetermined reference value and a poor prognosis when the expression level of the snoRNA HBII-239 or the has-miR-768 is lower than the predetermined reference value. DETAILED DESCRIPTION OF THE INVENTION:

Definitions:

Throughout the specification, several terms are employed and are defined following paragraphs.

As used herein, the term "PTCL" for "Peripheral T-Cell Lymphomas" denotes rare and heterogeneous non-Hodgkin's lymphoma (NHL) that, in general, are associated with a poor clinical outcome. PTCL are divided in two groups:

• "anaplastic PTCL" also called "ALCL" for "Anaplastic Large Cell Lymphoma" and;

• "non-anaplastic PTCL" also called "non-ALCL" for "non-Anaplastic Large Cell Lymphoma".

ALCL are also divided in two groups:

• "ALCL with anaplastic lymphoma kinase gene rearrangement" for "ALCL ALK+" and;

• "ALCL without anaplastic lymphoma kinase gene rearrangement" for "ALCL ALK-".

At last, non-anaplastic PTCL are also divided in two groups:

• "PTCL-NOS" for "Peripheral T-Cell Lymphoma Not Otherwise Specified" and;

• AITL for "Angio-Immunoblastic T-cell Lymphoma".

The method of the invention is particularly suitable for the duration of the progression- free survival (PFS) and/or the overall survival (OS).

As used herein, the term "progression-free survival" (PFS) denotes the length of time during and after medication or treatment during which the disease being treated does not get worse.

As used herein, the term "sample" refers to any tissue sample derived from the patient that contains nucleic acid materials. Said tissue sample is obtained for the purpose of the in vitro evaluation. The sample can be fresh, frozen, fixed (e.g., formalin fixed), or embedded (e.g., paraffin embedded). In a particular embodiment the sample results from biopsy performed in the tissue sample of the patient. In a particular embodiment the sample can be blood, serum, urine, T-lymphocytes or saliva. In a particular embodiment, the sample is blood.

As used herein, the term, snoRNAs for "Small nucleolar RNAs" denotes a class of small RNA molecules that primarily guide chemical modifications of other RNAs, mainly ribosomal RNAs, transfer RNAs and small nuclear RNAs. There are two main classes of snoRNA, the C/D box snoRNAs which are associated with methylation, and the H/ACA box snoRNAs which are associated with pseudouridylation. snoRNAs are commonly referred to as guide RNAs but should not be confused with the guide RNAs that direct RNA editing in trypanosomes. All the snoRNAs pertaining to the invention are known per se and sequences of them are publicly available from the data base http://www-snorna.biotoul.fr/index.php. The snoRNAs of the invention are listed in Table A:

U57 SR0000289

U76 SR0000033

U51 SR0000278

U21 SR0000020

U88 SR0000284

U71d SR0000294

U45A SR0000018

HBII-336 SR0000344

14q(I-5) SR0000095

ACA36B SR0000039

Table A: list of the snoRNAs according to the invention

As used herein, the term "miRNAs" has its general meaning in the art and refers to microRNA molecules that are generally 21 to 22 nucleotides in length, even though lengths of 19 and up to 23 nucleotides have been reported. miRNAs are each processed from a longer precursor RNA molecule ("precursor miRNA"). Precursor miRNAs are transcribed from non- protein-encoding genes. The precursor miRNAs have two regions of complementarity that enables them to form a stem-loop- or fold-back-like structure, which is cleaved in animals by a ribonuclease Ill-like nuclease enzyme called Dicer. The processed miRNA is typically a portion of the stem. The processed miRNA (also referred to as "mature miRNA") become part of a large complex to down-regulate a particular target gene. All the miRNAs pertaining to the invention are known per se and sequences of them are publicly available from the data base http://microrna.sanger.ac.uk/sequences/. The miRNAs of the invention are listed in Table B:

Table B: list of the miRNA according to the invention

Methods according to the invention A first object of the invention relates to a method for predicting the survival time of a patient suffering from a non-anaplastic PTCL comprising the steps consisting of:

i) measuring, in a sample obtained from the patient, the expression level of the snoRNA HBII-239 or the level expression of the has-miR-768;

ii) comparing said expression level with a predetermined reference value and;

iii) providing a good prognosis when the expression level of the snoRNA HBII-239 or the has-miR-768 is higher than the predetermined reference value and a poor prognosis when the expression level of the snoRNA HBII-239 or the has-miR-768 is lower than the predetermined reference value.

In a particluar embodiment according to the invention the expression levels of the snoRNA HBII-239 and the has-miR-768 are measuring together.

In another particular embodiment, the invention relates to a method for predicting the survival time of a patient suffering from an AITL comprising the steps consisting of:

i) measuring, in a sample obtained from the patient, the expression level at least one snoRNAs selected from the group consisting of HBII-239, U59B or U90;

ii) comparing said expression level with a predetermined reference value and;

iii) providing a good prognosis when the expression level of the selected snoRNAs is higher than the predetermined reference value and a poor prognosis when the expression level of the selected snoRNAs is lower than the predetermined reference value.

In oneembodiment, at least two snoRNAs selected from the group consisting of HBII- 239, U59B or U90 are measuring. In another embodiment, the snoRNAs HBII-239 and U59B or the snoRNAs HBII-239 and U90 or the snoRNAs U59B and U90 are measuring.

In a particular embodiment, the snoRNAs HBII-239, U59B and U90 are measuring together.

In another particular embodiment according to the invention, the invention relates to a method for predicting the survival time of a patient suffering from a PTCL-NOS comprising the steps consisting of

i) measuring, in a sample obtained from the patient, the expression level at least one snoRNA selected from the group consisting of HBII-239, U90, U80, ACA54, HBII-99, HBII- 438A, HBII-85-6, SNORA12, SNORD22, 14q(I-3) or U50B;

ii) comparing said expression level with a predetermined reference value and; iii) providing a good prognosis when the expression level of the selected snoRNAs is higher than the predetermined reference value and a poor prognosis when the expression level of the selected snoRNAs is lower than the predetermined reference value.

In oneembodiment, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11 snoRNAs are measured.

In another embodiment, the expression levels of the snoRNSs HBII-239, HBII-438A and U80 are measuring together.

A second aspect of the invention relates to a method for distinguish between ALCL and non-ALCL comprising the steps consisting of:

i) measuring, in a sample obtained form a patient, the expression level of at least one snoRNA selected from the group consisting of U75, ACA51, snord22, U57, U76, U51, U21, U88, U71d, U45A, 14q(I-3), HBII-336, 14q(I-5), ACA36B or U80.

ii) comparing said expression level with a predetermined reference value and;

iii) determining that the lymphoma is a non-ALCL when the expression level of the selected snoRNAs is higher than the predetermined reference value and determining that the lymphoma is an ALCL when the expression level of the selected snoRNAs is lower than the predetermined reference value.

In oneembodiment, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 snoRNAs are measured.

In anotherembodiment, the expression level of the snoRNA U75 is measuring.

A third aspect of the invention relates to a method for distinguish between ALCL ALK+ and ALCL ALK- comprising the steps consisting of:

i) measuring, in a sample obtained form a patient, the expression level of the snoRNA

U3;

ii) comparing said expression level with a predetermined reference value and;

iii) determining that the lymphoma is an ALCL ALK+ when the expression level of the selected snoRNAs is higher than the predetermined reference value and determining that the lymphoma is an ALCL ALK- when the expression level of the selected snoRNAs is lower than the predetermined reference value. According to the invention, measuring the expression level of the snoR As or the miRNA of the invention in the sample obtained from the patient can be performed by a variety of techniques.

For example the nucleic acid contained in the samples (e.g., cell or tissue prepared from the patient) is first extracted according to standard methods, for example using lytic enzymes or chemical solutions or extracted by nucleic-acid-binding resins following the manufacturer's instructions. The extracted snoRNAs or miRNAs is then detected by hybridization (e. g., Northern blot analysis) and/or amplification (e.g., RT-PCR). Preferably quantitative or semi-quantitative RT-PCR is preferred. Real-time quantitative or semi- quantitative RT-PCR is particularly advantageous. Other methods of Amplification include ligase chain reaction (LCR), transcription-mediated amplification (TMA), strand displacement amplification (SDA) and nucleic acid sequence based amplification (NASBA).

In a particular embodiment, the determination comprises contacting the sample with selective reagents such as probes or primers and thereby detecting the presence, or measuring the amount of snoRNAs or miRNAs originally in the sample. Contacting may be performed in any suitable device, such as a plate, microtiter dish, test tube, well, glass, column, and so forth. In specific embodiments, the contacting is performed on a substrate coated with the reagent, such as a snoRNAs or miRNA array. The substrate may be a solid or semi-solid substrate such as any suitable support comprising glass, plastic, nylon, paper, metal, polymers and the like. The substrate may be of various forms and sizes, such as a slide, a membrane, a bead, a column, a gel, etc. The contacting may be made under any condition suitable for a detectable complex, such as a snoRNAs or miRNAs hybrid, to be formed between the reagent and the snoRNAs or miRNAs of the sample.

Nucleic acids exhibiting sequence complementarity or homology to the snoRNAs or miRNAs of interest herein find utility as hybridization probes or amplification primers. It is understood that such nucleic acids need not be identical, but are typically at least about 80% identical to the homologous region of comparable size, more preferably 85% identical and even more preferably 90-95% identical. In certain embodiments, it will be advantageous to use nucleic acids in combination with appropriate means, such as a detectable label, for detecting hybridization. A wide variety of appropriate indicators are known in the art including, fluorescent, radioactive, enzymatic or other ligands (e. g. avidin/biotin).

The probes and primers are "specific" to the snoRNAs or miRNAs they hybridize to, i.e. they preferably hybridize under high stringency hybridization conditions (corresponding to the highest melting temperature Tm, e.g., 50 % formamide, 5x or 6x SCC. SCC is a 0.15 M NaCl, 0.015 M Na-citrate).

Accordingly, the present invention concerns the preparation and use of snoRNAs or miRNA arrays or snoRNAs or miRNA probe arrays, which are macroarrays or microarrays of nucleic acid molecules (probes) that are fully or nearly complementary or identical to a plurality of snoRNAs or miRNA molecules positioned on a support or support material in a spatially separated organization. Macroarrays are typically sheets of nitrocellulose or nylon upon which probes have been spotted. Microarrays position the nucleic acid probes more densely such that up to 10,000 nucleic acid molecules can be fit into a region typically 1 to 4 square centimeters. Microarrays can be fabricated by spotting nucleic acid molecules, e.g., genes, oligonucleotides, etc., onto substrates or fabricating oligonucleotide sequences in situ on a substrate. Spotted or fabricated nucleic acid molecules can be applied in a high density matrix pattern of up to about 30 non-identical nucleic acid molecules per square centimeter or higher, e.g. up to about 100 or even 1000 per square centimeter. Microarrays typically use coated glass as the solid support, in contrast to the nitrocellulose-based material of filter arrays. By having an ordered array of snoRNAs or miRNA-complementing nucleic acid samples, the position of each sample can be tracked and linked to the original sample. A variety of different array devices in which a plurality of distinct nucleic acid probes are stably associated with the surface of a solid support are known to those of skill in the art. Useful substrates for arrays include nylon, glass, metal, plastic, latex, and silicon. Such arrays may vary in a number of different ways, including average probe length, sequence or types of probes, nature of bond between the probe and the array surface, e.g. covalent or non-covalent, and the like.

After an array or a set of snoRNAs or miRNA probes is prepared and/or the snoRNAs or miRNA in the sample or snoRNAs or miRNA probe is labeled, the population of target nucleic acids is contacted with the array or probes under hybridization conditions, where such conditions can be adjusted, as desired, to provide for an optimum level of specificity in view of the particular assay being performed. Suitable hybridization conditions are well known to those of skill in the art and reviewed in Sambrook et al. (2001). Of particular interest in many embodiments is the use of stringent conditions during hybridization. Stringent conditions are known to those of skill in the art.

Alternatively, snoRNAs or miRNAs quantification method may be performed by using stem-loop primers for reverse transcription (RT) followed by a real-time TaqMan® probe. Typically, said method comprises a first step wherein the stem-loop primers are annealed to snoRNAs or miRNA targets and extended in the presence of reverse transcriptase. Then snoRNAs or miRNA-specific forward primer, TaqMan® probe, and reverse primer are used for PCR reactions. Quantitation of snoRNAs or miRNAs is estimated based on measured CT values.

Many snoRNAs or miRNA quantification assays are commercially available from

Qiagen (S. A. Courtaboeuf, France) or Applied Biosystems (Foster City, USA).

Expression level of a snoRNAs or miRNA may be expressed as absolute expression level or normalized expression level. Typically, expression levels are normalized by correcting the absolute expression level of a snoRNAs or miRNA by comparing its expression to the expression of a snoRNAs or miRNA that is not a relevant for predicting the survival time of a patient suffering from a non-anaplastic PTCL, e.g., a housekeeping snoRNAs that is constitutively expressed. Suitable snoRNAs for normalization include housekeeping snoRNAs such as the U8, U3, U2, U4 and U5. This normalization allows the comparison of the expression level in one sample, e.g., a patient sample, to another sample, or between samples from different sources.

Kits

A further object of the invention relates to kits for performing the methods of the invention, wherein said kits comprise means for measuring the expression level of the snoRNAS or miRNA of the invention in the sample obtained from the patient. The kits may include probes, primers macroarrays or microarrays as above described.

For example, the kit may comprise a set of snoRNAs or miRNA probes as above defined, usually made of DNA, and that may be pre-labelled. Alternatively, probes may be unlabelled and the ingredients for labelling may be included in the kit in separate containers. The kit may further comprise hybridization reagents or other suitably packaged reagents and materials needed for the particular hybridization protocol, including solid-phase matrices, if applicable, and standards.

Alternatively the kit of the invention may comprise amplification primers (e.g. stem- loop primers) that may be pre-labelled or may contain an affinity purification or attachment moiety. The kit may further comprise amplification reagents and also other suitably packaged reagents and materials needed for the particular amplification protocol. In a particular embodiment, the kit of the invention relates to a kit for predicting the survival time of a patient suffering from a non-anaplastic PTCL, comprising means for measuring, in a sample obtained from said patient, at least one snoRNAs selected from the group consisting of HBII-239, U90, U80, ACA54, HBII-99, HBII-438A, HBII-85-6, SNORA12, SNORD22, 14q(I-3), U50B ,U59B or the miRNA has-miR-768.

In another particular embodiment, the kit of the invention relates to a kit for distinguish between ALCL and non-ALCL, comprising means for measuring, in a sample obtained from said patient, at least one snoRNAs selected from the group consisting of U75, ACA51, snord22, U57, U76, U51, U21, U88, U71d, U45A, 14q(I-3), HBII-336, 14q(I-5), ACA36B or U80.

In another particular embodiment, the kit of the invention relates to a kit for distinguish between ALCL ALK+ and ALCL ALK-, comprising means for measuring, in a sample obtained from said patient, at least one snoRNAs selected from the group consisting ofU3.

In a particular embodiment, the kit of the invention relates to a kit which further comprise means for comparing the expression level of the snoRNAS or miRNA in the sample with a control, wherein detecting differential in the expression level of the snoRNAS or miRNA between the sample and the control is indicative of the survival time of a patient suffering from a non-anaplastic PTCL. The control may consist in sample associated with a healthy patient not afflicted with a non-anaplastic PTCL or in a sample associated with a patient afflicted with a non-anaplastic PTCL.

The invention will be further illustrated by the following figures and examples. However, these examples and figures should not be interpreted in any way as limiting the scope of the present invention.

FIGURES:

Figure 1: ALCL discloses a specific snoRNA profile. U3 snoR A expression level discriminates ALK-positive from ALK-negative ALCL cases.

Figure 2: Prognostic impact of snoRNA signatures in non-ALCL T-cell lymphoma subtypes.

(A) HBII-239, U90 and U59b relative expression in AITL-overexpressing cases (groupl) and other cases (group 2) compared to the median expression in all AITL. (B) OS and PFS Kaplan-Meyer analysis in group 2. (C) Relative expression of HBII-438A, U80 and HBII-239 in PTCL-NOS-overexpressing cases (groupl) and other cases (group 2) compared to the median expression in all PTCL-NOS samples. (D) OS and PFS Kaplan-Meyer analysis in group 2. (E) HBII-239 relative expression in all non-ALCL T-cell lymphoma cases compared to the median expression. (F) OS and PFS Kaplan-Meyer analysis in HBII-239 over-expressing cases (groupl) and other cases (group 2). (G) HBII-239 and HBII-239- processed microRNA (has-miR-768-3p) relative expression in 37 randomly selected non- ALCL T-cell lymphoma cases.

Non ALCL cases

n=26 n=46 n=78

NC: not communicated LDH indicates lactate dehydrogenase.

Total cohort of non ALCL cases included 6 rare diagnostics (HSTL, NK T and EATL)

ALCL cases

n=32

Table 1: Patient characteristics in PTCL.

Gene fold change P value filtered

U3 -1 .63 0.000000 *

ACA51 3.91 0.000000 *

snord22 1 .71 0.000000 *

snord44 -1 .77 0.000000 *

snord97 -3.74 0.000000 *

U57 1 .54 0.000000 *

U75 84.22 0.000000 *

U76 4.68 0.000000 *

U91 -3.38 0.000000 *

U51 3.15 0.000000 *

U21 2.32 0.000000 *

U88 5.76 0.000001 *

snorA73A -1 .45 0.000025 *

snorA38 -1 .90 0.000040 *

ACA54 -1 .71 0.000053 *

snord13 -1 .53 0.000062 *

ACA24 -1 .45 0.000173 *

U59b -1 .49 0.000211 *

ACA15 -1 .95 0.000213 *

snorA53 -1 .68 0.000236 *

U71d 1 .74 0.000263 *

U45A 1 .39 0.000277 *

U41 -1 .43 0.000377 *

14q(l-3) 16.96 0.000387 *

ACA12 -1 .88 0.000577 *

HBII-85-26 -1 .93 0.000688 *

HBII-336 1 .63 0.001962 *

14q(l-5) 7.53 0.005333 *

ACA36B 1 .69 0.007579 *

U80 2.17 0.034337 *

Table 2: Supervised snoRNA expression analysis demonstrated a set of 30 snoRNAs differentially expressed in ALCL cases compared to other PTCL subtypes. * indicates filtered genes according selected criterion (Fold Change>l .3 and p value <0.05).

EXAMPLE:

Material & Methods

Patients and healthy donors

PTCL samples (n=122) were collected from the tissue bank of the multicentric T-cell lymphoma consortium (TENOMIC) (Table 1). For each case, a consensus diagnosis was made by a panel of expert hemopathologists (some of the patients participated in a GELA- sponsored clinical trial; the others benefited from a national review protocol for T-cell lymphomas). T-lymphocytes from healthy donors (n=10) were collected from blood samples provided by the Etablissement Francais du Sang. Cells were sorted by CD3-positive selection on Miltenyi columns and cell purity was determined by flow cytometry (only purities over 94% were retained). Fresh and thawed samples were obtained with patients' informed consent and stored at the TENOMIC collection. According to French law, the TENOMIC collection is registered by the Ministry of Higher Education and Research and a transfer agreement was obtained after approval by the ethics committee (CCPPRB). Clinical and biological annotation of the samples was declared to the national committee on data processing and liberties Comite National Informatique et Libertes. Quantitative PCR method

Total RNA from patient samples and CD3-sorted T-lymphocytes were extracted using the trizol method and RNA integrity was evaluated using an Agilent Nano Chip (Agilent 2100 Bioanalyser). Only samples with an RIN over 7.8 were used in this study. All samples were reverse transcribed using Superscript II reverse transcription kit (Invitrogen) according to the manufacturer's protocol. The Fluidigm high-throughput quantitative PCR method (Biomark) was used as previously described28. Each primer used for this study was previously tested and amplification efficiency was over 85%. Relative RNA quantity was determined by the AACt method.

Hsa-miR-768-5p and -3p expression was quantified first by Taqman reverse transcription (Life Technologies), then by Taqman PCR quantification on an Applied 7300 thermocycler according to the manufacturer's protocol. The random selection of cases was carried out using http://www.randomizer.org/.

Building of the snoRNA chip

Eighty small non-coding RNAs were selected on the basis that they were: i) orphan snoRNAs, many of which are encoded by multiple, tandemly- arranged intronic variant genes (e.g: SNORD112-114 snoRNAs29); ii) already known as microRNA precursors (e.g: HBII- 239 snoRNA21,30); iii) previously linked to a medical condition (e.g: SNORD116 snoRNAs31); and iv) predicted to guide chemical modification of ribosomal RNA (http://www-snorna.biotoul.fr/). We also tested U8 and U3 snoRNAs because they are under the control of their own promoter. U2, U4 and U5 small nuclear RNAs corresponding to three spliceosomal machinery components were tested in parallel. Amongst the five housekeeping genes used on the snoRNA chips, S14 and 5s-rRNA displayed the lowest coefficient of variation. We selected the 5s-rRNA because of its similarity with snoRNAs (e.g. non-coding R A with similar length) and because this gene is widely used for non-coding R A normalization.

Statistical considerations

Dendrograms were generated by dChip software using correlation determination and the centroid method. A filter of gene expression was applied to all samples with a cut-off of about 0.25. Comparison of gene expression in each group of samples was done using a fold change cut-off above 1.3 and p<0.05. Specific gene expression comparison between each assigned group was then performed using an unpaired-t-test (p<0.05*; p<0.01 ** and pO.001 ***).

Progression- free survival (PFS) was calculated as time from diagnosis to first occurrence of progression or death or secondary malignancy or time of last patient contact if no event occurred. Overall survival (OS) time was calculated from diagnosis time until death or time of last contact if the patient was alive. The method of Kaplan-Meier was used to generate survival curves, and curves were compared using a Logrank test (MedCalc software).

Results Patient characteristics in PTCL [78 non-ALCL and 32 ALCL cases]

The distinct PTCL entities and their respective clinical characteristics are summarized in Table 1. From the 90 non-ALCL patients used in this study, full clinical records were available for 78 patients, of which 46 were diagnosed as AITL, 26 as PTCL-NOS, and 6 as rare entities [including enteropathy-associated T-cell lymphoma (EATL), hepatosplenic T-cell lymphoma (HSTL), or extranodal NK/T-cell lymphoma (NK/T)]. The median age of patients in the PTCL-NOS/AITL group was 67 years. Although a slightly better outcome for AITL cases was observed, the 3-year-OS and PFS were not significantly different between AITL and PTCL-NOS. Prognostic indexes were not significant and did not differentiate better prognosis patients (patients had intermediate-high and high risk IPI/ PIT scores in 74% and 65.5%, respectively). Initial therapy approaches varied widely, but 79% of patients received an active CHOP- or cytarabine-based regimen, 11.8% a combination of oral cyclophosphamide and steroids (for AITL), 2.6% a combination of oral fludarabine- cyclophosphamide, and 6.6% a palliative oral monotherapy (steroids, chlorambucil). Only 4/78 received upfront intensification with autologous (n=3) or allogeneic (n=l) bone marrow transplantation. Response rates for the non-ALCL patients included 44% CR (complete response), 18.2% PR (partial response), 7.8% stable disease, and 30% progressive disease. According to PTCL-NOS/AITL subgroups, response rates were, respectively: 38.5%/15.4%/11.5%/34.6% and 50%/17.4%/4.3%/28.3% (p>0.05), in accordance with previous data published on CHOP efficacy in PTCL5, 11 ,32.

ALCL cases were composed of 22 patients with ALK tyrosine kinase gene rearrangement (ALK+) and 10 patients without rearrangement (ALK-) (Table 1). As previously described, ALCL diagnoses were made in younger patients (median age of 13 years) and were associated with a good clinical outcome for ALK-positive cases (1 -year-OS of 94%) and a poor clinical outcome for ALK-negative cases (1-year-OS of 57%). Most patients were submitted to ALCL99-based treatment with complete recovery (CR) in 91% of cases.

SnoRNA expression profiles in the diagnosis of PTCL

In unsupervised hierarchical clustering, we observed that neoplastic cells displayed a significant global down-regulation of snoRNA expression compared to non-neoplastic T-cells [ranging from a 15% to 96% decrease in expression]. However, we noticed a significant over- expression of snoRNA U75, U76 and snRNA U2 in PTCL samples. Among PTCL entities, ALCL has a specific snoRNA profile. A significant differential expression of 30 snoRNAs was obtained when ALCL and non-ALCL cases were compared. SnoRNA expression comparison between ALCL ALK- and other PTCL subtypes confirmed a significant differential expression of 21 from the 30 snoRNAs. From these genes U75 snoRNA (belonging to the GAS5 snoRNA cluster) was the most powerful classifier in distinguishing ALCL from other PTCLs (table 2). Within the "core" group of ALCL, unsupervised clustering was not able to distinguish ALK- from ALK+ patients. However, a supervised comparison of snoRNA gene expression profile identified snoRNA U3 as discriminant marker that clearly distinguishes ALK+ from ALK- ALCL samples (Figure 1).

The unsupervised snoRNA signature did not allow us to distinguish AITL from the other subgroups of PTCL (NOS, EATL, NK/T, HSTL). Furthermore, a supervised comparison of snoRNA expression between PTCL-NOS and AITL failed to identify a specific profile. Altogether, snoRNA expression profile discriminates ALCL from other PTCL entities, and snoRNA U3 is statistically over-expressed in ALK+ compared to ALK- ALCL. Prognostic value of snoRNA expression in non-anaplastic PTCL

Although AITL and other PTCL subtypes appeared very similar regarding their snoRNA expression profiles, we observed that AITL/PTCL-NOS branches were subdivided into 3 groups upon unsupervised clustering. Eight snoRNAs were differentially expressed between these 3 groups of patients (each with a fold change greater than 1.5). Next, we analyzed the clinical features from the 78 patients. Interestingly, we observed that OS was significantly prolonged in the group over-expressing these 8 snoRNA genes. To further investigate the impact of snoRNAs on PTCL prognosis, we performed two separate supervised studies on PTCL-NOS and AITL, with a cut-off for OS analyses of 1 or 2 years, respectively (based on median survival: 13months and 26months, respectively).

Supervised comparison of snoRNA expression at two-year-OS in AITL confirmed the significant over-expression of HBII-239 (p=0.0162), U59B (p=0.0086) and U90 (p=0.0077) in patients with long-term survival (Figure 2A). Using Kaplan-Meier analysis, both PFS and OS were significantly improved in AITL patients who had over-expression of these 3 snoRNA genes (Figure 2B). Interestingly, overall response rates were not different between the two prognostic groups.

A similar approach was applied to PTCL-NOS. First a signature of 11 sno-RNAs, predictive of OS on univariate analysis, was found (HBII-239, U90, U80, ACA54, HBII-99, HBII-438A, HBII-85-6, SNORA12, SNORD22, 14q(I-3) and U50B) and narrowed down to the 3 most powerful predictors by increasing the stringency of snoRNA selection [HBII-239 (p=0.02), HBII-438A (p=0.003) and U80 (p= 0.044)] (Figure 2C). Again, Kaplan-Meier curves showed significantly different OS rates based on the level of snoRNA expression (Figure 2D). Nevertheless, the 3 snoRNA genes did not have a predictive impact on PFS. On the other hand, CR rates after CHOP were not significantly higher in the good prognosis group. Altogether, these data indicate that signatures with limited numbers of snoRNAs are strong predictors of OS (AITL, PTCL-NOS) and PFS (AITL), independent of IPI or PIT scores.

HBII-239 and HBII-239-processed microRNA-768: two powerful prognostic tools HBII-239 appears to be one of the most important snoRNAs, the over-expression of which predicts a good prognosis in AITL and PTCL-NOS in unsupervised and supervised analyses. We thus investigated its impact as a single marker on survival/outcome. Out of the entire cohort of 78 patients, HBII-239 over-expression was statistically associated with prolonged PFS and OS (Figure 2E and 2F). The HBII-239 sequence has been previously shown to overlap with the hsa-miR-768 precursor sequence. Incidentally, the has-miR-768 was removed from miRbase as it was considered that this microRNA is actually a snoRNA. We decided to evaluate whether the group of PTCL patients over-expressing HBII-239 showed a simultaneous over-expression of has-miR-768. MiR-768-5p and -3p Taqman microRNA assays on 37 randomly selected cases demonstrated a significant over-expression of this microRNA in the HBII-239 over- expressing group (a good prognostic group), and confirmed that only the 3p strand is processed into mature microRNA (Figure 2G). REFERENCES:

Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

Sabattini E, Bacci F, Sagramoso C, et al: WHO classification of tumours of haematopoietic and lymphoid tissues in 2008: an overview. Pathologica 102:83-7, 2010.

Iqbal J, Weisenburger DD, Greiner TC, et al: Molecular signatures to improve diagnosis in peripheral T-cell lymphoma and prognostication in angioimmunoblastic T-cell lymphoma. Blood 115: 1026-36, 2010.

Swerdlow SH CE, Harris NL, et al: WHO Classification: Pathology and Genetics of Tumors of Haematopoietic and Lymphoid Tissues., IARC Press, 2008.

Vose J, Armitage J, Weisenburger D: International peripheral T-cell and natural killer/T-cell lymphoma study: pathology findings and clinical outcomes. J Clin Oncol 26:4124-30, 2008.

Kerry J., Savage NLH, Julie M. Vose, Fred Ullrich, Elaine S. Jaffe, Joseph M. Connors, Lisa Rimsza,, Stefano A. Pileri MC, Randy D. Gascoyne, James O. Armitage and Dennis D. Weisenburger,: ALK- anaplastic large-cell lymphoma is clinically and immunopheno typically different from botbALK+ALCL and peripheral T-cell lymphoma, not otherwise specified: report from the International Peripheral T-Cell Lymphoma Project. Blood 111 :5496-5504, September 17, 2011.

Hammann WNaC: Small RNAs: Analysis and Regulatory Functions, Springer- Ver lag Berlin and Heidelberg GmbH & Co. K, 2005. Bachellerie JP, Cavaille J, Huttenhofer A: The expanding snoRNA world. Biochimie 84:775-90, 2002.

Dong XY, Guo P, Boyd J, et al: Implication of snoRNA U50 in human breast cancer. J Genet Genomics 36:447-54, 2009

Claims

CLAIMS:

1. A method for predicting the survival time of a patient suffering from a non-anaplastic Peripheral T-Cell Lymphomas (PTCL) comprising the steps consisting of i) measuring, in a sample obtained from the patient, the expression level of the snoRNA HBII-239 or the level expression of the has-miR-768, ii) comparing said expression level with a predetermined reference value and iii) providing a good prognosis when the expression level of the snoRNA HBII-239 or the has-miR-768 is higher than the predetermined reference value and a poor prognosis when the expression level of the snoRNA HBII-239 or the has-miR-768 is lower than the predetermined reference value.

2. A method for predicting the survival time of a patient suffering from a Angio- Immunoblastic T-cell Lymphoma (AITL) comprising the steps consisting of i) measuring, in a sample obtained from the patient, the expression level of at least one snoRNAs selected from the group consisting of HBII-239, U59B or U90 ii) comparing said expression level with a predetermined reference value and iii) providing a good prognosis when the expression level of the selected snoRNAs is higher than the predetermined reference value and a poor prognosis when the expression level of the selected snoRNAs is lower than the predetermined reference value.

3. A method for predicting the survival time of a patient suffering from a Peripheral T- Cell Lymphoma Not Otherwise Specified (PTCL-NOS) comprising the steps consisting of i) measuring, in a sample obtained from the patient, the expression level of at least one snoRNAs selected from the group consisting of HBII-239, U90, U80, ACA54, HBII-99, HBII-438A, HBII-85-6, SNORA12, SNORD22, 14q(I-3) or U50B, ii) comparing said expression level with a predetermined reference value and iii) providing a good prognosis when the expression level of the selected snoRNAs is higher than the predetermined reference value and a poor prognosis when the expression level of the selected snoRNAs is lower than the predetermined reference value.

4. A method according to the claim 3 wherein the selected snoRNSs are HBII-239, HBII- 438A and U80.

5. A method for distinguish between a Anaplastic Large Cell Lymphoma (ALCL) and a non- Anaplastic Large Cell Lymphoma (non-ALCL) comprising the steps consisting of i) measuring, in a sample obtained form a patient, the expression level of at least one snoRNAs selected from the group consisting of U75, ACA51, snord22, U57, U76, U51, U21, U88, U71d, U45A, 14q(I-3), HBII-336, 14q(I-5), ACA36B or U80, ii) comparing said expression level with a predetermined reference value and iii) determining that the lymphoma is a non-ALCL when the expression level of the selected snoRNAs is higher than the predetermined reference value and determining that the lymphoma is an ALCL when the expression level of the selected snoRNAs is lower than the predetermined reference value.

6. A method according to the claim 6 wherein the snoRNA is U75.

7. A method for distinguish between a Anaplastic Large Cell Lymphoma with anaplastic lymphoma kinase gene rearrangement (ALCL ALK+) and a Anaplastic Large Cell Lymphoma without anaplastic lymphoma kinase gene rearrangement (ALCL ALK-) comprising the steps consisting of i) measuring, in a sample obtained form a patient, the expression level of the snoRNA U3 ii) comparing said expression level with a predetermined reference value and iii) determining that the lymphoma is an ALCL ALK+ when the expression level of the selected snoRNAs is higher than the predetermined reference value and determining that the lymphoma is an ALCL ALK- when the expression level of the selected snoRNAs is lower than the predetermined reference value.

8. A method according to claims 1 to 7 wherein the sample is blood or T-lymphocytes.