Tissue nanomechanical signature for detection and prognosis of non-small-cell lung cancer

Abstract

In one aspect, the invention relates to a method to diagnose non-small-cell lung cancer. In another aspect, the invention relates to a method of the measurement of imminent aggressiveness and prediction of distant progression.

Description

[0001] Tissue Nanomechanical Signature for Detection and Prognosis of Non-Small-Cell Lung Cancer

[0002] Field iciii

[0003] The present invention relates to a method to diagnose non-small-cell lung cancer (NSCLC) and predict distant disease progression by detecting and analysing a nanomechanical signature in fresh core needle biopsy tissues from patients with NSCLC as collected during clinical standard of care.

[0004] Background

[0005] Lung cancer diagnosis and the differentiation of tumour entities, particularly between non-smallcell lung cancer (NSCLC) and other forms, significantly impacts treatment decisions and follow-up care. Diagnosis of lung cancer typically involves a combination of clinical assessment, imaging studies, and pathological evaluation. Clinical Assessment typically includes patient history, physical examination, and consideration of risk factors such as smoking history. Imaging studies may include methods such as chest X-ray, computed tomography (CT) scanning, and positron emission tomography (PET) scanning to identify lung abnormalities, assess tumour size, and detect possible metastases.

[0006] Lung cancer is primarily classified into two main types based on histological examination:

[0007] Non-Small-Cell Lung Cancer (NSCLC) is the most common type, accounting for about 85% of cases. NSCLC is further divided into several subtypes, including adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. The differentiation is based on the cellular appearance and molecular characteristics.

[0008] Small-Cell Lung Cancer (SCLC): This type is less common and is known for its rapid growth and early spread. It is treated differently from NSCLC due to its aggressive nature.

[0009] Molecular profiling has become increasingly important in differentiating lung cancer entities and guiding treatment. Techniques such as next-generation sequencing (NGS) are used to identify genetic mutations and alterations in cancer cells, such as EGFR mutations, ALK rearrangements, and ROS1 fusions in NSCLC. These molecular characteristics can significantly impact treatment decisions.

[0010] Treatment and Follow-Up Consequences differ depending on the tumour type. For NSCLC, treatment depends on the stage and molecular characteristics of the tumour. Options include surgery, radiation therapy, chemotherapy, targeted therapy (for tumours with specific genetic mutations), and immunotherapy. Molecular profiling of the tumour can lead to personalized treatment plans that improve outcomes. For SCLC, treatment typically involves chemotherapy and radiation therapy. Due to its aggressive nature, early and intensive treatment is necessary.

[0011] Follow-Up: Regular follow-up is crucial for lung cancer patients to monitor for recurrence, manage side effects of treatment, and detect second primary cancers. The frequency and nature of followup depend on the initial treatment, type of lung cancer, and stage at diagnosis.

[0012] The differentiation of lung cancer into specific entities, particularly NSCLC, and the detailed molecular profiling of tumours have profoundly impacted the treatment landscape, enabling more personalized and effective therapy approaches. Ongoing research and clinical trials continue to refine these strategies, offering hope for improved outcomes for lung cancer patients.

[0013] Complex structural remodelling of cells and extracellular matrix during cancer initiation and progression are accompanied by substantial biomechanical alterations, which can be measured by Atomic Force Microscopy (AFM). Increasing (pre)- and clinical evidence demonstrate the importance of cancer biomechanics in cancer diagnosis, assessment of imminent aggressiveness and prediction of disease progression.

[0014] Based on the above-mentioned state of the art, the objective of the present invention is to provide means and methods to detect and discriminate non-small cell lung cancer, assess the imminent aggressiveness in non-small-cell lung cancer and predict distant disease progression in non-small cell lung cancer. This objective is attained by the subject-matter of the independent claims of the present specification, with further advantageous embodiments described in the dependent claims, examples, figures and general description of this specification.

[0015] Summary of the Invention

[0016] In one aspect, the invention relates to a method to detect non-small-cell lung cancer (NSCLC). In an alternative aspect, the invention relates to a method for discriminating NSCLC from other types of cancer in a cancer patient sample. The method according to the invention comprises the steps of: subjecting a tissue sample obtained from a patient ex-vivo to nanomechanical profiling to obtain a tissue nanomechanical signature, and assigning to said sample a likelihood of being representative of non-small-cell lung cancer.

[0017] Another aspect of the invention relates to measurement of imminent aggressiveness on non-smallcell lung cancer and predict distant disease progression.

[0018] Yet another aspect of the invention relates to the a method to assign a treatment plan, based on the imminent aggressiveness rating and predicted probability of distant progression. This method comprises the steps of subjecting a cancer tissue sample obtained from a patient to ex-vivo nanomechanical profiling to obtain a tissue stiffness nanomechanical signature as specified herein; assigning to said patient a likelihood of o imminent aggressiveness; o the distant progression of the disease based on said nanomechanical signature assigning the patient to an aggressive treatment course to avoid distant disease progression if the likelihood of distant disease progression is high; assigning the patient to a de-escalating treatment course if the likelihood of distant disease progression is low.

[0019] Terms and definitions

[0020] General

[0021] For the purposes of interpreting this specification, the following definitions will apply and whenever appropriate, terms used in the singular will also include the plural and vice versa. In the event that any definition set forth below conflicts with any document incorporated herein by reference, the definition set forth shall control.

[0022] The terms “comprising”, “having”, “containing”, and “including”, and other similar forms, and grammatical equivalents thereof, as used herein, are intended to be equivalent in meaning and to be open-ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. For example, an article “comprising” components A, B, and C can consist of (i.e., contain only) components A, B, and C, or can contain not only components A, B, and C but also one or more other components. As such, it is intended and understood that “comprises” and similar forms thereof, and grammatical equivalents thereof, include disclosure of embodiments of “consisting essentially of or “consisting of.”

[0023] Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit, unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure.

[0024] Reference to “about” a value or parameter herein includes (and describes) variations that are directed to that value or parameter per se. For example, description referring to “about X” includes description of “X.” As used herein, including in the appended claims, the singular forms “a”, “or” and “the” include plural referents unless the context clearly dictates otherwise.

[0025] "And / or" where used herein is to be taken as specific recitation of each of the two specified features or components with or without the other. Thus, the term "and / or" as used in a phrase such as "A and / or B" herein is intended to include "A and B," "A or B," "A" (alone), and "B" (alone). Likewise, the term "and / or" as used in a phrase such as "A, B, and / or C" is intended to encompass each of the following aspects: A, B, and C; A, B, or C; A or C; A or B; B or C; A and C; A and B; B and C; A (alone); B (alone); and C (alone).

[0026] Unless defined otherwise, all medical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art (e.g., radiology, pathology, oncology, diagnosis, treatment optimisation, cancer). Standard techniques are used for molecular, genetic, and biochemical methods (see generally, Sambrook et al., Molecular Cloning: A Laboratory Manual, 4th ed. (2012) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. and Ausubel et al., Short Protocols in Molecular Biology (2002) 5th Ed, John Wiley & Sons, Inc.) and chemical methods.

[0027] Detailed Description of the Invention

[0028] Non-small cell lung cancer represents the leading cause of cancer related mortality worldwide, with extremely low disease free and overall survival rates. Therefore, early diagnosis and prediction of cancer aggressiveness holds the promise for improved clinical management of patients with NSCLC.

[0029] The inventors’ team at the University of Basel (Switzerland) optimized the indentation type AFM (IT-AFM) method for the measurement of tissue mechanical properties at nanoscale level in fresh clinical biopsies and developed first Automated and Reliable Tissue Diagnostics (ARTIDIS) investigational device for nanomechanical profiling of clinical biopsy samples at patient bedside. ARTIDIS technology has the distinctive capability to probe the topographical and mechanical properties of fresh human tissue samples in physiological environments at the nanometer level and generate spatial nanomechanical signature within <3h time frame. Most importantly ARTIDIS tissue analysis approach is completely non-destructive and tumor biopsies can enter standard diagnostic process after ARTIDIS measurement.

[0030] In one aspect, the invention relates to a method to detect non-small-cell lung cancer (NSCLC). In an alternative aspect, the invention relates to a method for discriminating NSCLC from other types of cancer in a cancer patient sample. The method according to the invention comprises the steps of: subjecting a tissue sample obtained from a patient to ex-vivo nanomechanical profiling to obtain a tissue nanomechanical signature, and assigning to said sample a likelihood of being representative of non-small-cell lung cancer. In certain embodiments, the tissue sample is a lung tissue sample.

[0031] In certain embodiments, obtaining the tissue nanomechanical signature entails measuring a plurality of stiffness values of the sample. In certain embodiments, obtaining the tissue nanomechanical signature entails measuring a plurality of adhesion values of the sample, as an alternative or addition to the stiffness values. In certain embodiments, obtaining the tissue nanomechanical signature entails measuring a plurality of dissipation values of the sample, as an alternative or addition to the stiffness and / or adhesion values.

[0032] In certain embodiments, the cancer tissue sample is obtained in the course of a standard of care clinical biopsy.

[0033] In another aspect, the invention relates to a method to rapidly assign a patient suspected of having non-small cell lung cancer to further diagnostic routine, or to a treatment schedule, comprising the steps of: subjecting a tissue sample obtained from the patient to ex-vivo nanomechanical profiling to obtain a tissue stiffness nanomechanical signature; assigning to the patient a likelihood of being diagnosed with non-small-cell lung cancer based on said nanomechanical signature.

[0034] The patient may then be further assigned to steps of diagnostic procedures, such as a CT scan, a PET scan, histologic profiling of the sample, further biopsy procedures or the like.

[0035] If the sample is assigned a high likelihood of representing a NSCLC sample, molecular profiling might be determined as a suitable follow-up diagnostic assay either from the same sample, or from a distinct sample that might need to be obtained. Molecular profiling might comprise genomic or RNA sequencing of the tumour and determination of genetic markers such as EGFR mutations, ALK rearrangements, and R0S1 fusions. In some embodiments, molecular profiling comprises determination of BRAF'J600E, KRASG12C, and ERBB2 (HER2) mutations, ALK, ROS1, NTRK 1 / 2 / 3, and RET fusions and / or MET exon-14 skipping mutations.

[0036] Different timepoints can be chosen to obtain the cancer biopsy tissue sample, depending on the clinical context in which the analysis is made. In certain embodiments the biopsy is taken in routine diagnostic settings, before the start of any treatment.

[0037] In certain embodiments the biopsy is taken during an on-going treatment, either as a first sample, or to allow following up on the analysis of a first sample having been obtained prior to commencement of treatment.

[0038] In certain embodiments the biopsy is taken in routine diagnostic setting and follow-up biopsies are taken during treatment. In case of biopsy following routine diagnosis (such as ultrasound, MRI, liquid biopsy, etc. that lead to taking a biopsy), there is not pre-selection of the patient, any biopsy is analysed with regard to its nanomechanical profile.

[0039] No control or healthy tissue is required. The components of the biopsy (cancer cells, stromal cells, immune cells, connective tissue, ... ) each carry their own characteristic signature and a modification or exchange of components changes to overall biopsy signature without the need for further control.

[0040] In certain embodiments, the nanomechanical profile is obtained by atomic force microscopy (AFM).

[0041] In certain embodiments, the nanomechanical profile comprises obtaining a plurality of tissue stiffness values by AFM measurement from the sample.

[0042] The whole biopsy is measured with "force maps" covering the complete sample, placing typically 10 to 30 maps, also depending on the biopsy size. At least 5 maps are taken. A single force map can be configured to measure typically 10 x 10 curves over 10 x 10 pm2up to 100 x 100 force curves over 100 x 100 urn2and combinations thereof.

[0043] The minimum amount of force curves is thus 100 force curves for a 10x10 map at 5 maps per biopsy, giving 500 force curves in total up to 12'000 force curves for example for 30 maps a 20x20 (400) force curves.

[0044] There is computation that extracts from raw force-distance curves a set of contact mechanics values, not limited to but, such as sample stiffness, elastic modulus, dissipation, adhesion and also surface topography. These derived contact mechanics values are used to derive thresholds or decision trees for predicting the response to a particular treatment.

[0045] In particular embodiments, the nanomechanical profile comprises 10 x 10 tissue stiffness values. In more particular embodiments, the nanomechanical profile comprises 20 x 20 or 24 x 24 tissue stiffness values. Even more particular embodiments have 50 x 50 or even 100 x 100 stiffness values.

[0046] In particular embodiments, the patient is assigned a high likelihood of being diagnosed with nonsmall cell lung cancer by the following decision making algorithm using indentation_backward_m_kurtosis_median and dissipation_approximation_IQR_median are: if (indentation_backward_m_kurtosis_median > 1.557e+00) and

[0047] (dissipation_approximation_IQR_median > 4.792e+02) then class: yes (proba: 91.67%) if (indentation_backward_m_kurtosis_median > 1.557e+00) and

[0048] (dissipation_approximation_IQR_median <- 4.792e+02) then class: no (proba: 76.92%) if (indentation_backward_m_kurtosis_median <- 1.557e+00) and

[0049] (indentation_backward_m_kurtosis_median <- 7.543e-01 ) then class: no (proba: 100.0%) if (indentation_backward_m_kurtosis_median <- 1.557e+00) and

[0050] (indentation_backward_m_kurtosis_median > 7.543e-01 ) then class: no (proba: 85.71 %) In particular embodiments, the patient is assigned a high likelihood of distant progression by the following decision making algorithm algorithm using using modulus_backward_N_m2_kurtosis_std and dissipation_only_skew_std are: if (dissipation_only_skew_std <- 1.328e+00) and (modulus_backward_N_m2_kurtosis_std > 1.644e+01 ) then class: no (proba: 100.0%) if (dissipation_only_skew_std <- 1.328e+00) and

[0051] (modulus_backward_N_m2_kurtosis_std <- 1.644e+01 ) then class: no (proba: 87.5%) if (dissipation_only_skew_std > 1.328e+00) and (dissipation_only_skew_std <- 1.852e+00) then class: yes (proba: 100.0%) if (dissipation_only_skew_std > 1.328e+00) and (dissipation_only_skew_std > 1.852e+00) no (proba: 50.0%)

[0052] Medical treatment and further procedures

[0053] Similarly, within the scope of the present invention is a method or treating lung cancer in a patient in need thereof, comprising: subjecting a tissue sample obtained from the patient to nanomechanical profiling to obtain a tissue stiffness nanomechanical signature, in an assignment step, assigning a probability of the absence or presence of NSCLC in said sample, administering to the patient standard of care NSCLC treatment.

[0054] The invention further entails assigning a patient to further diagnostic procedures depending on the outcome of the assignment step. Further diagnostic procedures may entail CET scanning, PET scanning, or molecular characterization of the tumour.

[0055] Thus, yet another aspect of the invention relates to a method of treatment of a patient having been diagnosed with aggressive non-small-cell lung cancer with the likelihood for distant progression subjecting a cancer tissue sample obtained from a patient ex-vivo to nanomechanical profiling to obtain a tissue stiffness nanomechanical signature as specified herein, assigning to said patient a likelihood of being responsive to standard of care treatment, applying more or less aggressive treatment modalities based on the imminent aggressiveness and likelihood of distant progression.

[0056] In particular embodiments, the treatment optimization by applying more or less aggressive treatment falls under the standard of care guideline.

[0057] The invention is further illustrated by the following examples and figures, from which further embodiments and advantages can be drawn. These examples are meant to illustrate the invention but not to limit its scope. Description of the Figures

[0058] Examples

[0059] Example 1:

[0060] Demonstration of the diagnostic power based on the following metrics: AUC of 0.87 using the following features: 'indentation_backward_m_kurtosis_median' 'adhesion_approximation_nN_std_median', 'applied_load_backward_N_skew_mean' 'plasticity_index_mean_mean', 'dissipation_approximation_IQR_median'

[0061] Performance metrics: Sensitivity: 0.84, Specificity: 0.81 , PPV: 0.79, NPV: 0.86, ACC: 0.82.

[0062] Demonstration of the difference between patients with and without disease progression, with the following metrics

[0063] Prior art documents:

[0064] US2014007309A1 (METHOD FOR STAGING CANCER PROGRESSION BY AFM; Plodinec et al., to Uni Basel).

[0065] US2017299570A1 (Method for predicting cancer progression by nanomechanical profiling; Loparic et al.; to Uni Basel)

[0066] US2020253590A1 (CORE BIOPSY NEEDLE; Plodinec et al., to Uni Basel).

[0067] US2015369838A1 (METHOD AND DEVICE FOR CONTROLLING A SCANNING PROBE MICROSCOPE; Lim et al. to Uni Basel).

[0068] All scientific publications and patent documents cited in the present specification are incorporated by reference herein.

Claims

Claims1 . A method for detecting non-small-cell lung cancer (NSCLC), or of discriminating NSCLC from other lung cancer types, said method comprising the steps of a. subjecting a tissue sample obtained from a patient to nanomechanical profiling to obtain a tissue stiffness nanomechanical signature, and b. assigning to said sample a likelihood of being representative of non-small-cell lung cancer.

2. A method to assign to a tissue sample a likelihood of representing a cancer disease of imminent aggressiveness, and to predict distant disease progression, said method comprising the steps of a. subjecting a tissue sample obtained from a patient to nanomechanical profiling to obtain a tissue stiffness nanomechanical signature, and b. assigning to said sample a likelihood of being representative of non-small-cell lung cancer.

3. The method according to claim 1 or 2, wherein the nanomechanical profile is obtained by atomic force microscopy (AFM).

4. The method according to any one of the preceding claims, wherein the nanomechanical profile comprises obtaining a plurality of tissue stiffness values by AFM measurement from the sample.

5. The method according to claim 4, wherein the plurality of tissue stiffness values obtained by AFM measurement comprises 10 x 10 tissue stiffness values.

6. The method according to claim 4, wherein the plurality of tissue stiffness values obtained by AFM measurement comprises 20 x 20, particularly 24 x 24 tissue stiffness values.

7. The method according to any one of the preceding claims, wherein the decision-making algorithms using indentation_backward_m_kurtosis_median and dissipation_approximation_IQR_median are: if (indentation_backward_m_kurtosis_median > 1 ,557e+00) and(dissipation_approximation_IQR_median > 4.792e+02) then class: yes (proba: 91.67%); if (indentation_backward_m_kurtosis_median > 1 ,557e+00) and (dissipation_approximation_IQR_median <- 4.792e+02) then class: no (proba: 76.92%);if (indentation_backward_m_kurtosis_median <- 1 ,557e+00) and (indentation_backward_m_kurtosis_median <- 7.543e-01 ) then class: no (proba: 100.0%); if (indentation_backward_m_kurtosis_median <- 1 ,557e+00) and (indentation_backward_m_kurtosis_median > 7.543e-01 ) then class: no (proba: 85.71 %); the biopsy is assigned a high likelihood of being malignant, particularly the biopsy is assigned a high likelihood of representing NSCLC.

8. The method according to any one of the preceding claims, wherein the decision-making algorithm using modulus_backward_N_m2_kurtosis_std and dissipation_only_skew_std are: if (dissipation_only_skew_std <- 1 ,328e+00) and (modulus_backward_N_m2_kurtosis_std > 1.644e+01 ) then class: no (proba: 100.0%); if (dissipation_only_skew_std <- 1 ,328e+00) and(modulus_backward_N_m2_kurtosis_std <- 1.644e+01 ) then class: no (proba: 87.5%); if (dissipation_only_skew_std > 1 ,328e+00) and (dissipation_only_skew_std <- 1.852e+00) then class: yes (proba: 100.0%); if (dissipation_only_skew_std > 1 ,328e+00) and (dissipation_only_skew_std > 1 ,852e+00) then class: no (proba: 50.0%) the patient is assigned a high likelihood of relapsing.