Micro array-based diagnostic and therapeutic device for identification of oncogenic mutations and assignment of targeted sirna therapies
Patent Information
- Application Number
- PCT/IB2026/053763
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2025-04-17
- Filing Date
- 2026-04-16
- Publication Date
- 2026-10-22
Abstract
Description
[0001] MICRO ARRAY-BASED DIAGNOSTIC AND THERAPEUTIC DEVICE FOR IDENTIFICATION OF ONCOGENIC MUTATIONS AND ASSIGNMENT OF TARGETED siRNA THERAPIESFIELD OF THE INVENTION
[0002] The present invention relates to the field of molecular diagnostics applied to oncology and, more particularly, to an integrated system based on microarray technology configured to identify specific oncogenic mutations in biological samples by molecular hybridization and to generate, through a local or remote processing system, an informative output comprising correlated therapeutic options.
[0003] In particular, the invention relates to a platform comprising at least one microarray support carrying capture probes, at least one device for reading hybridization signals and at least one digital library containing associated mutational and / or therapeutic information. In certain embodiments, the system may comprise computational algorithms configured to process additional clinical data and generate comparative classifications of possible therapeutic options.
[0004] The system is preferably configured to be updatable and scalable, in order to allow integration of new mutations, new biomarkers and / or further therapeutic options.
[0005] BACKGROUND ART
[0006] In the field of precision oncology, molecular characterization of a tumor represents a relevant element for guiding clinical decisions and personalizing treatment according to the genetic profile of the patient.
[0007] Microarray technologies are known and are used for gene expression analysis, for detecting specific mutations and for identifying molecular signatures associated with different tumor diseases. Such solutions generally allow production of molecular data, but frequently have static architectures and fragmented operational processes, in which the diagnostic detection phase and the subsequent therapeutic interpretation phase are separated.In many known systems, interpretation of the results obtained and identification of possible treatments remain substantially entrusted to specialized personnel. Furthermore, conventional systems do not satisfactorily provide simple mechanisms for physical updating of the diagnostic platform, such as to adapt rapidly to different tumor types or to the evolution of scientific knowledge.
[0008] Methods of analysis using microarrays are also known, comprising techniques for amplification of RNA transcripts, reverse transcription, use of universal or gene-specific primers and multiplex identification systems by barcode. However, such approaches are mainly directed to generation and quantification of molecular data, without describing an integrated system suitable for automatically correlating the results obtained with informational databases relating to candidate therapeutic options.
[0009] There therefore remains a need for a more flexible, updatable and integrated platform capable of combining molecular detection, automated data processing and generation of informative outputs usable in the clinical field.
[0010] SUMMARY OF THE INVENTION
[0011] In order to overcome at least in part the drawbacks described above, the present invention proposes a molecular analysis and decision support system based on microarray technology, configured to receive nucleic acids derived from a biological sample of the patient, detect by molecular hybridization the presence of specific oncogenic mutations, and automatically correlate the obtained data with information contained in at least one digital library.
[0012] In a preferred embodiment, the system comprises a microarray support carrying a plurality of capture probes arranged according to a predetermined spatial topology, an external reading device suitable for acquiring hybridization signals, and a processing system configured to associate the detected signals with respective coordinates of the microarray, identify the mutation present and generate an informative output containingthe results of the analysis and, optionally, comparative indications relating to possible therapeutic options.
[0013] A further aspect of the invention relates to the modular structure of the analysis support. In certain embodiments, the microarray may comprise physically removable, replaceable or updatable modules suitable for containing subsets of probes dedicated to specific pathological classes, tumor groups or mutational panels. This allows the system to be adapted to clinical needs and the platform to be kept updated without completely replacing the reading device.
[0014] In further embodiments, each module may comprise an identifier automatically readable by the system, such as to allow recognition of the installed module and automatic retrieval of associated digital topographic maps, operating configurations and / or informational libraries.
[0015] The system may further comprise remote updating functionalities of the digital databases, as well as computational modules based on statistical models, machine learning or artificial intelligence, configured to process predictive parameters and generate comparative classifications of candidate therapeutic options.
[0016] Among the technical advantages achievable by the invention are: integration of multiple operational phases into a single platform, reduction of workflow fragmentation, greater updatability of the physical and digital components, reduction of technological obsolescence, and improved adaptability to the needs of precision medicine.
[0017] Therefore, an object of the present invention is:
[0018] • an integrated molecular analysis system as described in the claims;
[0019] • a method of using said system for generating informative outputs based on the results of molecular analysis;
[0020] • a computer program product comprising instructions adapted to execute the functions of the system.DETAILED DESCRIPTION OF THE INVENTION
[0021] The present invention relates to a molecular analysis and decision support system for oncological applications, comprising:
[0022] a) an analysis support configured to host a plurality of capture probes arranged according to a predetermined spatial topology, said probes being configured to selectively hybridize with target nucleic acids derived from a biological sample of a subject, in order to detect the presence of one or more oncogenic mutations;
[0023] b) at least one physically detachable and replaceable detection module operatively associated with said analysis support, said module comprising a subset of said capture probes dedicated to a mutation panel specific for a predetermined pathological class or tumor group;
[0024] c) an acquisition device configured to detect hybridization signals generated on the analysis support and to convert said signals into digital data comprising spatial localization information;
[0025] d) a data processing system in communication with the acquisition device, comprising at least one digital correlation map adapted to associate the spatial localization information with mutational identities and at least one digital library containing information correlated with the detected mutational identities and, in certain embodiments, with candidate therapeutic options;
[0026] wherein the system is configured to operate as a decision support tool without direct physical administration of therapeutic agents.
[0027] The general operation of the system comprises preparation of the biological sample according to techniques known to a person skilled in the art, contacting the sample withthe analysis support, detecting the signals generated by molecular hybridization, converting the signals into digital data, associating the data with the coordinates of the support and generating an informative output containing the results of the analysis.
[0028] In one embodiment, the biological sample is selected from tissue biopsy, liquid biopsy, peripheral blood, plasma, serum, circulating tumor cells, cytological samples or other suitable biological materials. The analyzable nucleic acids comprise genomic DNA, RNA, mRNA, microRNA, cDNA, circulating tumor DNA (ctDNA), circulating free DNA (cfDNA), amplified nucleic acids and / or combinations thereof.
[0029] In one embodiment, the analysis support comprises a plurality of capture probes configured to selectively hybridize with one or more of the above nucleic acids, in order to detect oncogenic mutations, gene fusions, splicing variants, copy number alterations, gene expression profiles, epigenetic markers or further molecular biomarkers.
[0030] In one embodiment, the microarray support comprises oligonucleotide probes or equivalent probes configured to selectively hybridize with molecular targets comprising RNA, DNA, cDNA, sequences associated with methylation states, transcripts representative of gene expression levels, microRNA or combinations thereof.
[0031] In one embodiment, the processing system is configured to correlate the detected biomarkers with information contained in at least one digital library comprising candidate informational or therapeutic options selected from siRNA, shRNA, antisense oligonucleotides, therapeutic miRNA, targeted pharmacological agents, immunotherapies, therapeutic combinations or correlated clinical protocols.
[0032] In one embodiment, tumor genetic material obtained from RNA may be subjected to reverse transcription and, where appropriate, amplification using techniques compatible with rapid and decentralized operational workflows, including point-of-care applications.The analysis support may consist of a microarray comprising a plurality of functional regions arranged according to a predetermined spatial configuration. Each region may comprise at least one oligonucleotide sequence complementary to a specific target sequence associated with an oncogenic mutation, splicing variant, gene fusion, copy number variation, gene expression signature, microRNA or further molecular biomarker.
[0033] In certain embodiments, the support comprises a hierarchical structure of cells and microcells, wherein each cell is associated with a target gene or biomarker and each microcell is associated with a specific molecular variant of the respective target.
[0034] The support may be made on substrates selected from glass, silicon, polymers, composite materials, coated supports, membranes or functionalized hydrogels.
[0035] The capture probes may be deposited by spotting, in situ synthesis, chemical immobilization, microdroplet deposition or equivalent techniques.
[0036] In one embodiment, the physically replaceable detection module comprises a removable material element carrying a subset of the probe panel of the main support. The module may be configured as a cartridge, insert, plate, sub-panel or equivalent element.
[0037] The removable module may be dedicated to specific pathological classes or tumor groups, including lung, breast, colorectal, prostate tumors, melanomas, hematological malignancies or further pathological classes.
[0038] Removable association of the module with the base support or with the reading device may occur by magnetic coupling, sliding guide, press-fit coupling, snap-fit housing, insertable cartridge, elastic coupling or further equivalent means.
[0039] In one embodiment, the module comprises a machine-readable identifier selected from optical code, QR code, barcode, RFID tag, electronic memory or equivalents, suitable for allowing automatic recognition of the installed module.Following recognition of the module, the system may automatically retrieve at least one data structure associated with the module, comprising a topographic map, operating parameters, dedicated digital library, predefined analysis profiles or combinations thereof.
[0040] The system may further verify the presence of installed modules, detect free and occupied locations and check compatibility among a plurality of modules simultaneously present.
[0041] The acquisition device may be implemented as a portable or benchtop unit and comprise at least one sensor selected from CMOS camera, CCD, photodiode, optical sensor, electrochemical sensor, impedance sensor or combinations thereof.
[0042] The detected signals may be fluorescent, chemiluminescent, colorimetric, electrical or of another nature compatible with the adopted detection technology.
[0043] The acquisition device may comprise an image processing module configured to perform one or more operations selected from detection of active regions, thresholding, segmentation, noise filtering, signal quantification, spatial registration and correction of translations, rotations or misalignments of the support.
[0044] The data processing system may be integrated into the acquisition device or located on an external local or remote unit, connected by wired or wireless network.
[0045] The digital correlation map associates the coordinates of the analysis support with corresponding molecular identities. In this way, the system translates the position of the detected signal into usable biological information.
[0046] The digital library may comprise data relating to mutations, clinical relevance, biological classifications, scientific references, candidate therapeutic options, validation levels, ranking, decision criteria or combinations thereof.The processing engine may comprise computational modules based on deterministic logic, expert systems, statistical models, artificial intelligence, machine learning or combinations thereof.
[0047] Said computational modules may use clinical data of the subject, anamnesis data, biological characteristics of the sample, previous treatments, molecular co-alterations or further parameters, in order to generate comparative classifications, priorities, rankings or informational suggestions.
[0048] The output generated by the system may comprise one or more identified mutations, detected biomarkers, informational classifications, correlated therapeutic candidates, documentary references, validation levels or further information useful to the clinician.
[0049] The output may be displayed, printed, stored or exported in an electronic format selected from PDF, XML, JSON, HL7, FHIR or further formats interoperable with healthcare information systems.
[0050] In one embodiment, the system comprises internal controls selected from positive controls, negative controls, spike-in RNA, reference sequences, calibration regions or process markers, in order to verify quality of the sample, hybridization and detection.
[0051] In one embodiment, the system is configured to process simultaneously a plurality of biological samples and generate distinct outputs for each sample.
[0052] The digital libraries and processing software may be updated locally or remotely through a communication network, preferably with version management, authentication, traceability and integrity verification.
[0053] In further embodiments, the system may receive clinical data subsequent to the initial analysis, comprising therapeutic response, biochemical parameters, adverse events orfurther follow-up data, in order to update at least part of the informational criteria or computational models used.
[0054] In one embodiment, the system comprises a plurality of locations configured to simultaneously receive a plurality of distinct microarray modules, each module being associated with a machine-readable unique identifier containing at least information relating to module identity, internal spatial configuration, installation position, version of the associated digital library and correspondence between hybridization regions and represented molecular targets.
[0055] The processing system is configured to automatically read said identifiers, determine the installed modules and their respective positions, generate a composite map of the analysis support and associate the detected signals with the local coordinates of each module and with the global coordinates of the system.
[0056] In this way, signals coming simultaneously from a plurality of modules may be automatically converted into distinct mutational identities and correlated with respective information contained in the digital library and / or therapeutic library.
[0057] In certain embodiments, the system may be commercialized in the form of a kit comprising at least one analysis support and / or replaceable module, one or more reagents for sample preparation, extraction, amplification and / or reverse transcription of nucleic acids, paper or digital operating instructions and, optionally, access credentials to processing software.
[0058] A further object of the invention is a molecular analysis method comprising the steps of: a) providing an analysis support comprising capture probes arranged according to a predetermined configuration;
[0059] b) applying to the support a biological sample containing target nucleic acids;
[0060] c) allowing hybridization between the sample and the capture probes;d) acquiring at least one signal generated by the hybridization and determining its spatial localization;
[0061] e) associating the spatial localization with at least one molecular identity by means of a digital map;
[0062] f) querying at least one associated digital library; and
[0063] g) generating an informative output containing the results of the analysis.
[0064] A further object of the present invention is a computer program product comprising instructions which, when executed by a data processing system operatively connected to an acquisition device, cause execution of the method described above.
[0065] In one embodiment, the analysis module comprising the microarray support is configured as a disposable or limited-use component, whereas the reading device is configured as a reusable unit.
[0066] In one embodiment, the system comprises positive, negative and / or calibration control regions adapted to verify correct hybridization, quality of the biological sample and correct operation of the reading device.
[0067] In one embodiment, the system is configured to perform a preliminary automatic calibration by acquisition of reference regions present on the analysis module, in order to set at least one of spatial alignment, background level, detection sensitivity, exposure time and reading parameters.
[0068] In one embodiment, the module comprises a plurality of reaction chambers or separate areas adapted to receive simultaneously a plurality of biological samples.
[0069] In one embodiment, the system is configured to process simultaneously a plurality of samples and generate distinct outputs for each sample.In one embodiment, the module is removably associated with the reading device by magnetic coupling, sliding guide, press-fit coupling, cartridge, elastic coupling or equivalent reversible connection means.
[0070] In one embodiment, automatic recognition of the module determines loading of operating parameters specific to the module itself.
[0071] In one embodiment, said operating parameters comprise at least one of scanning area, resolution, exposure time, gain, detection threshold, analysis algorithm, optical filter or acquisition time.
[0072] In one embodiment, the data processing system generates a comparative classification of informational or therapeutic options as a function of detected biomarkers, signal intensity, molecular co-alterations, anamnesis data, previous treatments or clinical profiles of the subject.
[0073] In one embodiment, the system receives subsequent clinical data and updates at least part of the digital library, correlation criteria or ranking parameters.
[0074] In one embodiment, the digital libraries are remotely updatable through a network connection with version control, authentication, traceability and integrity verification.
[0075] In one embodiment, the system is configured to generate an output within a predetermined time from receipt of the sample, preferably within 48 hours.
[0076] In one embodiment, the reading device performs automatic correction of translation, rotation or misalignment of the module with respect to a nominal position.
[0077] In one embodiment, each removable module is configured to be positioned on the support by predetermined housing locations comprising at least one mechanical centering element selected from guides, stops, pins, optical references, magnets, interlocks or combinationsthereof, so as to ensure correct spatial orientation and repeatable correspondence between the physical coordinates of the module and the associated digital map.
[0078] Example 1 - Molecular analysis workflow of the system
[0079] In an exemplary embodiment, a tumor sample taken from a patient is subjected to RNA extraction and subsequent reverse transcription, and optionally amplification, in order to obtain a tumor cDNA sample. This sample is brought into contact with the microarray chip, on which sequences representative of relevant oncogenic mutations are immobilized. Following molecular hybridization between the tumor cDNA and the sequences present on the chip, detectable signals are generated by a reading system, for example of optical or electrochemical type, associated with the areas of the microarray in which selective binding has occurred.
[0080] The reader converts these signals into digital data and transmits them to the processing system, which, by means of a preconfigured digital map of the coordinates of the microarray, associates each signal with the corresponding target sequence, so as to identify the oncogenic mutation present in the sample. Once the mutation has been identified, the system may query one or more digital libraries to confirm the identity and clinical relevance of the mutation itself and to correlate it with a plurality of siRNA-based therapeutic candidates. In certain embodiments, the processing may also use computational algorithms configured to refine such correlation based on clinical and genomic data of the patient.
[0081] The system then generates an informative output comprising at least the detected mutation, one or more correlated therapeutic candidates and, optionally, further indications relating to validation level, scientific references or alternative options. The clinician receives said output and evaluates its possible use within the therapeutic decision-making process.
[0082] Example 2 - Organization of the chip into cells and microcellsIn a further exemplary embodiment, the chip is configured as a planar microstructured grid organized into cells and microcells. Each cell is associated with a gene of oncological interest, whereas each microcell constitutes a sub -compartment of the respective cell and is functionalized with an oligonucleotide sequence complementary to a specific mutational variant of the corresponding gene.
[0083] The system may be configured so that, for the same gene, a plurality of microcells represents a plurality of known mutations. In a representative example, a cell dedicated to the p53 gene comprises microcells corresponding to mutations R175H, R248Q, R273C and R282W. During hybridization, the tumor cDNA of the patient selectively binds to the microcell corresponding to the mutation actually present in the tumor. The reading system detects the exact position of the signal, while the digital mapping module associates said position with the gene and the corresponding mutational variant.
[0084] This hierarchical organization allows simultaneous mapping of a high number of genes and mutational variants within a single test, generating an integrated diagnostic and informative output.
[0085] Example 3 - Signal processing and output generation
[0086] In an exemplary embodiment, after the hybridization phase the chip is read by an external portable or benchtop device, provided with an optical scanner or a fluorescence, chemiluminescence or other equivalent detection sensor. The reader acquires the posthybridization image and subjects it to software processing by means of an image processing module suitable for detecting the position of activated microcells and quantifying the intensity of the corresponding signal.
[0087] Signal processing may comprise thresholding, segmentation, spatial registration with respect to the topographic map of the chip, background noise filtering and signal intensity quantification. In a subsequent phase, the digital mapping module associates thecoordinates of the active microcells with a target gene and a specific oncogenic mutation, optionally using relational, NoSQL or equivalent data structures.
[0088] The informational correlation is then performed by querying the digital library, which may contain, for each therapeutic candidate, information relating to sequence, documented efficacy, validation level and available evidence. In certain embodiments, the system may further apply ranking criteria or computational modules based on clinical and genomic data, so as to return to the physician an informative output comprising the identified mutation and the correlated therapeutic options.
[0089] Example 4 - Digital memory, chip identification and system updatability
[0090] In a possible embodiment, the chip is associated with a digital identity, for example by QR code, RFID or passive EEPROM microchip, which allows the reader to automatically recognize the internal topographic map of the microarray and retrieve the information associated with the corresponding configuration. In this way, the reader may access the correspondences between microcell, mutation and correlated digital information, as well as the version of the available libraries.
[0091] In one embodiment, the diagnostic library comprises sequences representative of validated oncogenic mutations, whereas a therapeutic digital library, stored locally or remotely accessible, links each identified mutation to correlated therapeutic candidates. In a further embodiment, the system is configured to be updated both physically and digitally: the microarray may be updated by introducing new sequences or replacing modules, whereas the digital libraries may be remotely updated, also by synchronization with clinical and scientific databases. This configuration allows the system to be kept aligned with the evolution of genomic and therapeutic knowledge.
[0092] Example 5 - Chip modularity and personalization by tumor classesIn a further exemplary embodiment, the system has a modular architecture in which the chip may be personalized according to specific tumor classes or different diagnostic contexts. In this configuration, individual cells or portions of the microarray containing groups of oncogenic sequences may be made removable and replaceable, so as to constitute autonomous modules insertable into a housing of the main chip or of a base support.
[0093] Each module may contain a subset of genes or mutations relevant to a given diagnostic context, thereby allowing replacement or updating of only the module concerned without requiring replacement of the entire reading system. The reader, preferably configured as a universal device, is able to read and interpret different compatible chips or modules by means of the integrated software and the associated digital map.
[0094] In further variants, modularity may also be implemented by programmable or regenerable surfaces, selective spotting on dedicated areas or configurations in which the chip is intended for single use. The modularity of the system therefore allows the content of the microarray to be adapted to diagnostic needs, facilitates updating of the mutational panel and reduces obsolescence of the platform.
[0095] Example 6 - Internal controls and follow-up phase
[0096] In an additional embodiment, the chip comprises internal molecular controls, such as spike-in RNA, reference sequences, calibration probes or process markers, intended to verify correctness of hybridization and quality of the diagnostic analysis. The reading system is configured to detect not only signals relating to oncogenic targets, but also signals relating to the controls, thereby allowing internal verification of reliability of the test.
[0097] In a subsequent phase of clinical use, the system may also be employed for monitoring and follow-up of the patient. For this purpose, clinical data subsequent to the start of treatment, such as tumor response, biochemical parameters, possible adverse effects orphenotypic variations, may be entered into the platform manually or by integration with clinical or laboratory information systems.
[0098] Such data may be processed by the system in order to compare clinical outcomes with previous analyses, update the informational databases and progressively improve the decision support capability of the system with respect to subsequent patients having similar molecular profiles.
[0099] Example 7 - Automatic recognition of the module and operating configuration
[0100] In an exemplary embodiment, a physically replaceable microarray module is associated with the analysis support or inserted into the reading device and is automatically identified by a machine-readable identifier selected from QR code, barcode, RFID tag, electronic memory, EEPROM microchip or equivalent means.
[0101] Following recognition of the installed module, the processing system automatically retrieves at least one data structure associated with the module itself, comprising a topographic map of the microarray, information relating to the represented molecular targets, correlated digital libraries and / or dedicated processing profiles.
[0102] In certain embodiments, the system automatically configures a plurality of operating parameters selected from scanning area, acquisition resolution, exposure time, integration time, detection threshold, sensor gain, selection of optical filters, processing algorithm or further functional settings of the reading device.
[0103] This automatic configuration reduces operating errors, simplifies use of the system, improves reproducibility of the analysis and accelerates switching between different diagnostic modules.
[0104] Example 8 - Disposable module and reusable readerIn a further exemplary embodiment, the analysis support comprising the microarray is configured as a disposable or limited-use module or cartridge, whereas the reading device is configured as a reusable unit intended for a plurality of analysis cycles.
[0105] The disposable module may comprise at least one surface functionalized with capture probes, optional control regions, reaction chambers and means for automatic identification of the module. After execution of the test, the module is removed from the reading device and replaced with a new module intended for a subsequent biological sample.
[0106] In certain embodiments, the reading device retains the processing logic, the optical or electronic acquisition system, the digital libraries and software modules, whereas the consumable component is represented only by the replaceable analysis module.
[0107] This configuration allows reduction of operating costs, containment of crosscontamination risk, greater logistical simplicity and higher scalability of clinical or laboratory use of the system.
[0108] Example 9 - Simultaneous use of multiple modules
[0109] In an exemplary embodiment, a first module dedicated to lung tumors is installed in a first location, while a second module dedicated to therapeutic resistance mechanisms is installed in a second location. After reading the identifiers of the modules, the system automatically loads the respective topographic maps and associated libraries. During scanning, a signal detected in the first module is associated with an EGFR mutation, while a signal detected in the second module is associated with a MET amplification. The system automatically generates an integrated output comprising both molecular alterations and the related correlated informational or therapeutic options. The software identifies the mutations through multi-level hierarchical mapping:
[0110] 1. identification of the module;
[0111] 2. position of the module in the chip;3. local coordinates of the signal within that module;
[0112] 4. translation into global coordinates;
[0113] 5. database lookup —> mutation / biomarker / therapy.
[0114] Example 10 - Embodiment of automatic multi-module operation
[0115] In an exemplary embodiment, the analysis support comprises a first location, a second location and a third location configured to receive three distinct modules, respectively. In an operating configuration, a first module dedicated to lung tumors is installed in the first location, a second module dedicated to therapeutic resistance mechanisms is installed in the second location, and a third module dedicated to quality controls and complementary biomarkers is installed in the third location.
[0116] Each module is provided with a machine-readable unique identifier containing at least the module code, the local topographic map, the list of represented targets, the nominal installation position and the version of the associated digital library. At the start of the analysis, the system automatically reads the identifiers of the three modules, determines that the three locations are occupied, verifies compatibility among the installed modules and loads the respective data structures.
[0117] The system then generates a composite map of the analysis support, in which the local coordinates of the individual modules are integrated into a global coordinate system. During the acquisition phase, the reading device detects a plurality of signals coming simultaneously from the three modules. A first signal, localized in the first location, is transformed into local coordinates of the first module and associated with an EGFR mutation; a second signal, localized in the second location, is transformed into local coordinates of the second module and associated with a MET amplification; a third signal, localized in the third location, is interpreted as an internal quality control.
[0118] The system then queries the digital library and / or therapeutic library associated with the identified targets, retrieves information relating to the EGFR mutation and METamplification, and automatically generates an integrated output comprising both molecular alterations, their origin from distinct modules, the corresponding informational references and the correlated informational or therapeutic options. The quality control detected in the third module is used to confirm overall validity of the analysis.
[0119] In further embodiments, the system may use simultaneous modules dedicated respectively to primary tumor profile, resistance mutations, prognostic biomarkers, internal controls, follow-up or therapeutic panels, generating a single integrated result even in the presence of a plurality of local maps and targets distributed in different modules.
[0120] FURTHER PREFERRED EMBODIMENTS
[0121] In one embodiment, the analysis module comprising the microarray support is configured as a disposable or limited-use component, whereas the reading device is configured as a reusable unit.
[0122] In one embodiment, the reading device comprises at least one sensor selected from CMOS camera, CCD sensor, photodiode, electrochemical sensor, impedance sensor or combinations thereof.
[0123] In one embodiment, the reading device comprises an optical system configured to detect fluorescent, chemiluminescent, colorimetric or equivalent signals.
[0124] In one embodiment, the analysis support comprises positive, negative and / or calibration control regions adapted to verify correct hybridization, quality of the biological sample and / or correct operation of the reading device.
[0125] In one embodiment, the system is configured to perform preliminary automatic calibration by reading reference regions present on the support or on the installed module.In one embodiment, the analysis support comprises a plurality of reaction areas adapted to receive simultaneously a plurality of biological samples.
[0126] In one embodiment, the system is configured to process simultaneously a plurality of biological samples and generate distinct outputs for each analyzed sample.
[0127] In one embodiment, the microarray support comprises at least one substrate selected from glass, silicon, polymer, composite material, coated substrate or functionalized hydrogel.
[0128] In one embodiment, the module is removably associated with the reading device by magnetic coupling, sliding guide, press-fit coupling, cartridge, elastic coupling or equivalent reversible connection means.
[0129] In one embodiment, automatic recognition of the module determines loading of operating parameters specific to the module itself.
[0130] In one embodiment, said operating parameters comprise at least one of scanning area, resolution, exposure time, sensor gain, detection threshold, optical filter, analysis algorithm or acquisition time.
[0131] In one embodiment, the system comprises a plurality of modules respectively dedicated to different pathological classes selected from lung, breast, colorectal, prostate tumors, melanomas, hematological malignancies or further oncological pathologies.
[0132] In one embodiment, the system is configured to detect, in addition to point mutations, one or more alterations selected from gene fusions, splicing variants, copy number variations, gene expression signatures, microRNA and epigenetic markers.
[0133] In one embodiment, the digital library comprises informational correlations with agents selected from siRNA, shRNA, antisense oligonucleotides, therapeutic miRNA, equivalent interfering RNAs or combinations thereof.In one embodiment, the data processing system generates a comparative classification, predictive scoring or ranking of candidate informational or therapeutic options as a function of detected biomarkers, signal intensity, molecular co-alterations, anamnesis data, previous treatments or further clinical profiles of the subject.
[0134] In one embodiment, the system receives subsequent clinical data and updates at least part of the digital library, correlation criteria or ranking parameters.
[0135] In one embodiment, the digital libraries are remotely updatable through a network connection with version control, authentication, traceability and integrity verification.
[0136] In one embodiment, the generated report is exportable in PDF, HL7, FHIR, XML, JSON or other formats interoperable with healthcare information systems.
[0137] In one embodiment, the system is configured to generate an informational output within a predetermined time from receipt of the biological sample, preferably within 48 hours, more preferably within 24 hours.
[0138] In one embodiment, the reading device performs automatic correction of translation, rotation or misalignment of the module with respect to a nominal position.
[0139] At any point in the present description and in the claims, the term “comprising” may be replaced, where technically appropriate, by “consisting of’ or “consisting essentially of’.
[0140] AUTOMATIC MANAGEMENT OF A PLURALITY OF MODULES AND MULTI-MODULE MAPPING PROCESS
[0141] In one embodiment, the system comprises an analysis support provided with a plurality of locations, housings, slots or installation areas configured to simultaneously receive a plurality of distinct microarray modules. Each module is preferably associated with amachine-readable unique identifier selected, by way of non-limiting example, from QR code, barcode, RFID tag, electronic memory, EEPROM microchip or equivalent identification means.
[0142] In one embodiment, said unique identifier of the module contains, directly or by reference to a local or remote memory, at least part of the following information: module identity, analytical panel type, pathological group or tumor class of reference, internal spatial configuration of the module, expected or permitted orientation of the module, installation position on the analysis support, version of the associated topographic map, version of the associated digital library, correspondence between capture regions and represented molecular targets, acquisition operating parameters and / or calibration data.
[0143] In one embodiment, following installation of a plurality of modules on the analysis support, the processing system performs an automatic procedure for recognizing the installed modules. This procedure may comprise sequential or parallel reading of the unique identifiers of the modules, determination of occupied and unoccupied locations, verification of compatibility among simultaneously present modules and retrieval of the respective associated data structures.
[0144] In one embodiment, for each recognized module, the system retrieves at least one local digital map of the module itself. This local map defines the arrangement of the capture regions, cells and / or microcells present in the module, as well as the correspondence between each local position and the respective target molecule, biomarker, mutation, splicing variant, gene fusion, copy number alteration, microRNA, epigenetic marker or other represented alteration.
[0145] In one embodiment, the system also determines the position of the individual module within the overall analysis support, thereby defining a relationship between the local coordinate system of the module and a global coordinate system of the support. In this way, each module is described not only by its own internal topography, but also by aspatial offset, an origin position, an orientation and / or a geometric transformation allowing its integration into a composite map of the system.
[0146] In one embodiment, the processing system automatically generates a multi-module composite map obtained by combining:
[0147] a) identification of the module;
[0148] b) position of the module in the installation location;
[0149] c) local spatial configuration of the module;
[0150] d) any orientation of the module;
[0151] e) correspondence between capture regions and molecular targets.
[0152] In one embodiment, said composite map allows each hybridization region detectable on the overall analysis support to be univocally associated with:
[0153] i) a specific location or slot of the support;
[0154] ii) a specific installed module;
[0155] iii) a specific local coordinate within the module;
[0156] iv) a specific molecular identity stored in the corresponding digital library.
[0157] In one embodiment, during the acquisition phase, the reading device detects signals coming from the plurality of installed modules, generating digital data comprising at least spatial position information and, preferably, also signal intensity information. In certain embodiments, the reading device acquires an overall image of the analysis support containing simultaneously the signals coming from multiple modules; in further embodiments, the modules may be read sequentially but nevertheless processed within the same composite map.
[0158] In one embodiment, the processing system is configured to perform a spatial registration procedure adapted to correct possible mechanical misalignments, rotations, translations, scale variations, module positioning errors or other geometric deviations with respect to a nominal position. For this purpose, the system may use alignment markers, referenceregions, internal controls, known geometric patterns or other calibration elements present on the support or on the individual modules.
[0159] In one embodiment, once the misalignments have been corrected and the global position of each detected signal has been determined, the system converts the global coordinate of the signal into a local coordinate of the module to which it belongs. Said transformation may be performed by applying offsets, transformation matrices, registration parameters or other suitable mathematical or geometric relationships.
[0160] In one embodiment, the local coordinate thus obtained is then used to query the local map of the corresponding module, in order to identify the specific activated capture region and the corresponding molecular target. In this way, the system automatically traces back, for each signal, to the oncogenic mutation, biomarker or other molecular alteration represented at the local position of the module in which the signal was detected.
[0161] In one embodiment, the molecular identity thus determined is then used to query at least one digital library associated with the module and / or with the overall system. Said digital library may contain, by way of example, information relating to biological or clinical relevance of the biomarker, classification of the molecular target, bibliographic references, validation criteria, candidate informational or therapeutic options, predictive rankings, correlated clinical protocols or combinations thereof.
[0162] In certain embodiments, the system is configured to query, in addition to the general library of the system, also a plurality of module-specific libraries, each of which is dedicated to the targets represented in the corresponding installed module. In further embodiments, the system may query a centralized therapeutic library containing the correspondence between a plurality of biomarkers and a plurality of candidate informational or therapeutic options selected from siRNA, shRNA, antisense oligonucleotides, therapeutic miRNA, targeted pharmacological agents, immunotherapies, therapeutic combinations or correlated clinical protocols.In one embodiment, when the hybridization signals come simultaneously from a plurality of modules, the processing system generates an integrated multi-module output, in which the results deriving from the different modules are collected, normalized, ordered and presented in unified form. In such integrated output, each result may be associated at least with:
[0163] a) module of origin;
[0164] b) installation location of the module;
[0165] c) local and / or global coordinate of the signal;
[0166] d) detected mutational identity or biomarker;
[0167] e) correlated clinical or therapeutic information;
[0168] f) any priority, ranking or relevance level.
[0169] In one embodiment, the system may further integrate the results coming from multiple modules to generate a combined evaluation of the molecular profile of the sample. For example, alterations detected in different modules may be treated as co-alterations, concomitant molecular events, resistance indicators or composite profiles, and used by the processing system to produce a broader comparative classification of the candidate informational or therapeutic options.
[0170] In one embodiment, the system is configured to avoid conflicts or interpretation ambiguities between different modules by means of logical priorities, compatibility rules, precedence tables, consistency checks or data fusion procedures. For example, where two different modules contain capture regions relating to partially overlapping targets, the system may assign priority to the more specific module, the more updated module, the signal having higher intensity or to a predefined validation criterion.
[0171] In one embodiment, the system may further automatically verify consistency between the physical configuration of the installed modules and the loaded data structures, preventing processing in the event of mismatch between module identifier, map version, library version or configuration of the installation location.In one embodiment, the processing system is configured to associate each result with a traceable data structure comprising at least the module identifier, the location identifier, the identified molecular target, the version of the library used, the date and / or time of the analysis, as well as any adopted acquisition parameters. This allows complete traceability of the multi-module analytical process.
[0172] In one embodiment, the system may generate a final report in which the results coming from a plurality of modules are presented as individual distinct entries or as an integrated overall molecular profile. The report may comprise, in addition to the detected alterations, indications relating to module of origin, confidence level, clinical relevance and correlated informational or therapeutic options.
Claims
CLAIMS1. An ex vivo molecular analysis and informative output generation system, comprising:a) an analysis support comprising a plurality of spatially distributed capture regions configured to interact with target nucleic acids derived from a biological sample;b) at least one removable module operatively associable with the analysis support and comprising a subset of said capture regions; c) an acquisition device configured to detect signals generated by the analysis support and to convert said signals into digital data comprising spatial position information;d) a data processing system in communication with the acquisition device and configured to:i) associate the digital data with spatial coordinates of the analysis support; ii) identify at least one molecular biomarker present in the biological sample on the basis of said association;iii) retrieve, from at least one digital memory, information associated with the identified biomarker;iv) generate an informative electronic output.
2. The system according to claim 1, wherein the removable module comprises a machine-readable identifier and the processing system is configured to automatically recognize the installed module and retrieve digital data associated therewith.
3. The system according to claim 2, wherein automatic recognition of the module determines automatic setting of at least one operating parameter selected from scanning area, resolution, exposure time, detection threshold, sensor gain, optical filter, analysis algorithm, or acquisition time.
4. The system according to any one of the preceding claims, wherein the processing system is configured to perform automatic spatial registration of the acquired data with respect to a reference map of the analysis support.
5. The system according to any one of the preceding claims, wherein the analysis support comprises main cells associated with respective target genes and microcells associated with respective molecular variants.
6. The system according to any one of the preceding claims, comprising a plurality of different removable modules dedicated to respective pathological groups or different molecular panels.
7. The system according to any one of the preceding claims, wherein the processing system comprises a computational module configured to classify or rank a plurality of informational records associated with the identified biomarker.
8. The system according to any one of the preceding claims, wherein the digital memory is remotely updatable through a communication network.
9. The system according to any one of the preceding claims, wherein the electronic output is exportable in an interoperable format selected from PDF, HL7, FHIR, XML, J SON, or equivalents thereof.
10. The system according to any one of the preceding claims, wherein the removable module is disposable or intended for limited use and the acquisition device is reusable.
11. An ex vivo molecular analysis method comprising the steps of:a) placing a biological sample into contact with an analysis support comprising spatially distributed capture regions;a) detecting signals generated by interaction between the biological sample and said capture regions;b) converting the signals into digital data comprising spatial information; c) associating the digital data with coordinates of the analysis support;d) identifying at least one molecular biomarker;e) retrieving, from a digital memory, information associated with the identified biomarker;f) generating an informative electronic output.
12. A removable module usable in a system according to any one of the preceding claims, comprising:a) a substrate;b) a plurality of spatially distributed capture regions on the substrate;c) at least one machine-readable identifier associated with the module.
13. The module according to claim 12, configured as an insertable cartridge removably couplable to an acquisition device.
14. The module according to claim 12 or 13, further comprising positive, negative, or calibration control regions.
15. A computer program product comprising instructions which, when executed by at least one processor, cause execution of the method according to claim 11.
16. A kit comprising:a) at least one module according to any one of claims 12-14;b) a system according to any one of claims 1-10;c) at least one reagent for preparation of the biological sample; andd) operating instructions.
17. The system according to any one of the preceding claims, wherein the analysis support comprises a plurality of seats configured to simultaneously receive a plurality of physically detachable detection modules, and wherein the data processing system is configured to:a) automatically identify installed modules by respective machine-readable identifiers thereof;b) determine the position of each module on the analysis support;c) generate a composite map comprising coordinates of a plurality of installed modules;d) associate hybridization signals detected from said modules with respective mutational identities;e) generate an integrated informative output comprising results derived from a plurality of modules.