Tissue nanomechanical signature predicts neoadjuvant treatment response

Abstract

In one aspect, the invention relates to a method to predict outcome of neoadjuvant therapy for a patient, comprising the steps of: - subjecting a cancer tissue sample obtained from a patient ex-vivo to nanomechanical profiling to obtain a tissue stiffness nanomechanical signature; - assigning to said patient a likelihood of being responsive to neoadjuvant therapy based on said nanomechanical signature. In another aspect, the invention relates to a method of treatment of cancer, particularly breast cancer, the method comprising obtaining a tissue stiffness nanomechanical signature from a tumour sample obtained from the patient, predicting the patient's responsiveness to neoadjuvant therapy, and administering neoadjuvant therapy based on the treatment.

Description

[0001] Tissue Nanomechanical Signature Predicts Neoadjuvant Treatment Response

[0002] Description

[0003] Field

[0004] The present invention relates to a method to predict the outcome of neoadjuvant cancer treatment by detecting and analysing a nanomechanical response profile in an isolated cancer tissue sample.

[0005] Background

[0006] 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 mediating therapy response. Incorporating AFM measurements of clinical biopsies within standard of care is thus a promising avenue to leverage tissue mechanics as prognostic and predictive biomarker for solid cancers.

[0007] Neoadjuvant treatment (NAT) modalities are increasingly used for pre-operative clinical management of early and locally advanced breast cancer (BC). Indications of NAT are several, including shrinking inoperable tumor in size and turning it to operable, reducing extent and morbidity of curative surgery, guiding breast-conserving surgery and using NAT response as a predictive marker for adjuvant treatment selection for improved disease free and overall survival (DFS and OS) of breast cancer patients. Classically, various combinations of chemo-Zradiotherapy, as well as targeted and hormone therapy have been used in NAT setting. Recently, the use of Immune Checkpoint Inhibitor (ICPi) Pembrolizumab has been approved by United States Food and Drug Administration (US FDA) together with chemotherapy for the use as NAT in early Triple Negative Breast Cancer (TNBC), followed by adjuvant pembrolizumab, based on the results of KEYNOTE- 522 clinical trial. The trial demonstrated excellent 3y DFS and OS. However, long term outcomes of the study are not yet mature, and still about 60% of all BC patients fail to respond NAT. Routinely used clinicopathological parameters, such as tumor size, Ki67 proliferation index, hormone receptor (HR) and Her2 status are only suboptimal to predict treatment response and none of the potential novel biomarkers demonstrated clinical utility so far. For example, tumor assessment of PD-L1 and tumor infiltrating lymphocytes (TILs) suffer from high interobserver variability, radiomics still represent a subject for debate due to inconsistent findings, liquid biopsy assessments such as ctDNA and CTCs did not demonstrate reliable clinical utility, and the value of various genomic tests, used in adjuvant setting (EndoPredict, Oncotype DX, MammaPrint, PAM50, etc.), is not yet certain in NAT setting. In addition, genetic testing remains time consuming and less cost efficient, and is therefore not accessible for all patients. Faster methods, facilitating choice of treatment, as well as early resistance prediction, could guide improved preoperative management of BC in more patients and reduce unnecessary toxicities from NAT.

[0008] Cancer biomechanical properties have recently emerged as a potential marker for cancer aggressiveness, progression, and therapy response. Naruse et al., coined the term mechanomedicine in 2013 to describe the medical applications of investigated mechanobiological changes mainly in reproductive and regenerative medicine. However, the terminology is also widely applicable in oncology. Various pre-clinical evidence demonstrates that cellular and extracellular matrix (ECM) stiffness play an important role in cancer therapy response. Generally, cancer cells are much softer than the cells of the tissue of the origin and the scale of cell softness reflects the level of malignant transformation. Contrary, the ECM becomes stiffer during malignant transformation and is generally characterized with high mechanical heterogeneity. Soft cancer cells are prone to migration and metastasis, whilst the specific mechanical arrangement of heterogenous ECM contributes to cancer cell directional migration. Joice at al., (2018) demonstrated an increased resistance to doxorubicin treatment in triple negative BC cell lines in stiff ECM microenvironment. In addition, Liu at al., (2021) showed that cancer cell softness prevents tumor cell killing by cytotoxic T-cells. Experimental data also showed the modulation of different treatment responses according to cell and / or ECM stiffness (reviewed by Deville et al., 2019). However, the findings across studies are not always consistent, potentially attributed to different methods used for measuring cell mechanical properties.

[0009] Our 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.

[0010] The objective of the study was to investigate whether ARTIDIS nanomechanical signature (NS) from baseline tissue biopsies can identify breast cancer patients that will respond to neoadjuvant therapy (NAT), independent of BC molecular subtype and / or treatment regimen. This is the substudy under a first prospective trial using ARTIDIS medical device, with the primary objective to assess the diagnostic potential of the nanomechanical signature in breast cancer patients (primary end-point results are due to be published separately).

[0011] We hypothesized that as tumor mechanical properties have a global influence on cancer aggressiveness, progression, and therapy response, which is not limited to one signaling pathway or one type of treatment, ARTIDIS nanomechanical signature might be able to differentiate NAT responders versus non-responders independent of BC subtype and applied NAT regimen. The overarching goal of such an investigation is to first generate the first clinical evidence about the power of ARTIDIS nanomechanical signature in differentiating potential NAT treatment response in baseline tissue biopsies, which will be validated and further optimized in larger clinical dataset, and eventually implemented in clinical practice as a predictive test for the assessment of NAT response in patients with BC, allowing personalized BC care, improved patient outcomes and overall improved quality of life. The investigation of tumor stiffness related treatment response in clinical setting has never been performed before.

[0012] Based on the above-mentioned state of the art, the objective of the present invention is to provide means and methods to predict neoadjuvant treatment outcomes in cancer patients. 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.

[0013] Summary of the Invention

[0014] In one aspect, the invention relates to a method to predict outcome of neoadjuvant therapy for a patient, particularly for a patient with a suspected malignant lesion, comprising the steps of: subjecting a cancer tissue sample obtained from a patient ex-vivo to nanomechanical profiling to obtain a tissue stiffness nanomechanical signature; assigning to said patient a likelihood of being responsive to neoadjuvant therapy based on said nanomechanical signature.

[0015] In another aspect, the invention relates to a method of treatment of cancer, particularly breast cancer, the method comprising obtaining a tissue stiffness nanomechanical signature from a tumour sample obtained from the patient, predicting the patient’s responsiveness to neoadjuvant therapy, and administering neoadjuvant therapy based on the treatment.

[0016] Terms and definitions

[0017] General

[0018] For 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.

[0019] 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.”

[0020] 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.

[0021] 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.”

[0022] As used herein, including in the appended claims, the singular forms “a”, “or” and “the” include plural referents unless the context clearly dictates otherwise.

[0023] "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).

[0024] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art (e.g., in cell culture, molecular genetics, nucleic acid chemistry, hybridization techniques and biochemistry, organic synthesis). 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.

[0025] The term “neoadjuvant therapy” or “neoadjuvant treatment’ in the context of the present specification, particularly when used in the context of breast cancer, relates to the administration of systemic therapy (including for example, but not being limited to, chemotherapy, targeted therapy, or hormone therapy) before the primary treatment for breast cancer, which typically involves surgery.

[0026] The term “targeted therapy’ in the context of the present specification, particularly when used in the context of breast cancer, relates to a type of treatment that specifically targets the molecular or genetic abnormalities within cancer cells. Unlike traditional chemotherapy, which acts on rapidly dividing cells, targeted therapy is designed to interfere with the specific proteins, receptors, or signalling pathways that play a crucial role in the growth and spread of cancer cells. In breast cancer, targeted therapies may be used to treat specific subtypes of the disease that have well-defined molecular characteristics. Some common examples of targeted therapies in breast cancer treatment include, but are not limited to:

[0027] HER2-Targeted Therapy: Human epidermal growth factor receptor 2 (HER2) is overexpressed in some breast cancers. Targeted therapies like trastuzumab (Herceptin), pertuzumab (Perjeta), and ado-trastuzumab emtansine (Kadcyla) specifically target HER2-positive breast cancer cells.

[0028] CDK4 / 6 Inhibitors: Cyclin-dependent kinase 4 / 6 (CDK4 / 6) inhibitors, such as palbociclib (Ibrance) and ribociclib (Kisqali), target the cell cycle and are used in hormone receptor-positive, HER2-negative breast cancers.

[0029] Hormone Therapy: hormone therapy specifically targets hormone receptor-positive breast cancers by blocking the effects of estrogen, which fuels the growth of these tumors. Medications like tamoxifen and aromatase inhibitors are commonly used in this context. PI3K Inhibitors: Some breast cancers may have mutations in the PIK3CA gene, leading to the activation of the PI3K pathway. PI3K inhibitors like alpelisib (Piqray) can specifically target this pathway in certain cases.

[0030] The choice of targeted therapy depends on the specific characteristics of the patient's breast cancer, as determined through molecular testing of the tumor. Targeted therapies are often used in combination with other treatments, such as chemotherapy or surgery, to achieve the best possible outcome in breast cancer management.

[0031] The term “endocrine therapy’ in the context of the present specification refers to drug treatment aimed at inhibiting the growth of hormone receptor-positive breast tumors.

[0032] The term “taxane” in the context of this specification relates to a class of chemotherapy drugs commonly used in the context of cancer treatment. They are derived from the bark of the Pacific yew tree, but several synthetic versions have been developed for medical use. Taxanes are effective against a variety of cancer types and are used to inhibit the growth and spread of cancer cells. Taxanes include but are not limited to frequently used taxane drugs used in cancer treatment such as:

[0033] Paclitaxel (Taxol)

[0034] Docetaxel (Taxotere)

[0035] Cabazitaxel (Jevtana).

[0036] The term “anthracycline” in the context of this specification relates to anthracycline cancer treatment drugs, such as doxorubicin and epirubicin, which are potent chemotherapeutic agents that exert their anti-cancer effects through a complex mechanism involving intercalation into DNA strands, inhibition of topoisomerase II, and the generation of free radicals. These actions result in DNA damage, interference with DNA replication, and ultimately, the induction of apoptotic cell death. Anthracyclines are widely utilized in the treatment of various malignancies, including breast cancer, lymphomas, and certain types of leukemia, due to their ability to target rapidly dividing cancer cells.

[0037] The term “Her-2 targeting drug” in the context of this specification includes drugs that target HER2 (human epidermal growth factor receptor 2). These drugs can be categorized into two main classes: HER2-targeted monoclonal antibodies and HER2-targeted small molecule inhibitors. Non-limiting examples of these drugs include:

[0038] HER2-Targeted Monoclonal Antibodies: o Trastuzumab (Herceptin): Trastuzumab was one of the first HER2 -targeted drugs and remains a cornerstone of treatment for HER2-positive breast cancer. It works by binding to the HER2 receptor, inhibiting its signaling and promoting immune-mediated destruction of HER2-positive cancer cells. o Pertuzumab (Perjeta): Pertuzumab is often used in combination with trastuzumab and chemotherapy to treat HER2-positive breast cancer. It targets a different region of the HER2 receptor, further inhibiting its activity. o T-DM1 (Ado-Trastuzumab Emtansine, Kadcyla): T-DM1 is an antibodydrug conjugate that combines trastuzumab with a cytotoxic drug. It delivers the chemotherapy directly to HER2-positive cancer cells, reducing damage to healthy cells. o Lapatinib (Tykerb): Lapatinib is a small molecule inhibitor that targets both HER2 and the epidermal growth factor receptor (EGFR). It is used in combination with capecitabine or letrozole for the treatment of HER2-positive breast cancer.

[0039] HER2-Targeted Small Molecule Inhibitors: o Trastuzumab Emtansine (T-DM1 , Kadcyla): T-DM1 is an antibody-drug conjugate, which combines trastuzumab with a cytotoxic drug. It delivers the chemotherapy directly to HER2-positive cancer cells, reducing damage to healthy cells. o Lapatinib (Tykerb): Lapatinib is a small molecule inhibitor that targets both HER2 and the epidermal growth factor receptor (EGFR). It is used in combination with capecitabine or letrozole for the treatment of HER2- positive breast cancer.

[0040] Detailed Description of the Invention

[0041] The invention relates to a method to predict outcome of neoadjuvant therapy for a patient, particularly for a patient with a suspected malignant lesion, comprising the steps of: subjecting a cancer tissue sample obtained from a patient ex-vivo to nanomechanical profiling to obtain a tissue stiffness nanomechanical signature; this step comprises obtaining a plurality of tissue stiffness values by AFM measurement from the sample. Typical AFM scans are conducted on a matrix of 10 x 10, 20 x 20, 24 x 24, or even higher numbers such as 50 x 50 or even 100 x 100 points. assigning to said patient a likelihood of being responsive to neoadjuvant therapy based on said nanomechanical signature.

[0042] In particular embodiments, the nanomechanical profile is obtained by atomic force microscopy (AFM).

[0043] In particular embodiments, the patient is a breast cancer patient.

[0044] In particular embodiments, the patient is assigned a high likelihood of being a responder to neoadjuvant therapy.

[0045] In particular embodiments, the high likelihood of being a responder to neoadjuvant therapy is assigned based on the nanomechanical signature.

[0046] In particular embodiments, the patient is assigned a high likelihood of being a responder to neoadjuvant endocrine therapy.

[0047] In particular embodiments, the patient is assigned a high likelihood of being a responder to neoadjuvant chemotherapy.

[0048] In particular embodiments, the high likelihood of being a responder to neoadjuvant chemotherapy is assigned based on the nanomechanical signature.

[0049] In particular embodiments, the neoadjuvant chemotherapy comprises administration of a taxane.

[0050] In particular embodiments, the neoadjuvant chemotherapy comprises administration of an anthracycline drug.

[0051] In particular embodiments, the neoadjuvant chemotherapy comprises administration further comprises administration of a Her-2 targeting drug.

[0052] In particular embodiments, the patient is predicted to be pathology CR (in complete remission) radiology CR.

[0053] The primary goals of neoadjuvant therapy are:

[0054] Tumor Shrinkage: Neoadjuvant therapy is administered to reduce the size of the primary breast tumor. This makes it more manageable and may enable breast-conserving surgery (lumpectomy) instead of mastectomy in some cases.

[0055] Assessment of Treatment Response: It allows clinicians to assess how well the tumor responds to the therapy. This information can help guide further treatment decisions.

[0056] Eradication of Microscopic Disease: Neoadjuvant therapy can help eradicate potential microscopic cancer cells in the lymph nodes and at distant sites before surgery.

[0057] Tailoring Treatment: The response to neoadjuvant therapy can inform the selection of subsequent treatments, such as additional chemotherapy or targeted therapy, and may help personalize the treatment plan based on the specific characteristics of the tumor. Neoadjuvant therapy is often recommended for certain breast cancer subtypes, particularly in cases where the tumor is large or aggressive. It allows fora more comprehensive and individualized approach to breast cancer treatment. The response to neoadjuvant therapy, determined by changes in tumor size and other clinical indicators, is used to assess the success of the treatment and to make informed decisions regarding the subsequent steps in the patient's treatment plan.

[0058] Neoadjuvant therapy is used in the treatment of various cancers beyond breast cancer. It is a common approach in oncology for several types of malignancies. The main principles of neoadjuvant therapy remain the same: administering systemic treatments such as chemotherapy, targeted therapy, or radiation therapy before the primary treatment, which is often surgery, with the aim of improving outcomes or making the surgical intervention more effective. Some examples of neoadjuvant therapy in other types of cancer include:

[0059] Colorectal Cancer: Neoadjuvant therapy is used to shrink large tumors in the colon or rectum before surgery. It can include chemotherapy and radiation therapy, making the tumor more resectable and potentially improving long-term outcomes.

[0060] Esophageal Cancer: Neoadjuvant therapy, usually a combination of chemotherapy and radiation therapy, is employed to shrink esophageal tumors before surgical resection. This can improve the chances of complete tumor removal.

[0061] Pancreatic Cancer: Neoadjuvant therapy, typically chemotherapy, is used to reduce the size of pancreatic tumors and improve the likelihood of complete surgical removal, as pancreatic cancer is often diagnosed at an advanced stage.

[0062] Lung Cancer: In some cases, neoadjuvant chemotherapy or radiation therapy is employed for locally advanced lung cancer to reduce tumor size before surgery, or even in cases where surgery may not be feasible.

[0063] Bladder Cancer: Neoadjuvant chemotherapy can be used before surgery to treat muscle- invasive bladder cancer. This can help shrink tumors and increase the chances of successful surgery.

[0064] Ovarian Cancer: In the case of advanced ovarian cancer, neoadjuvant chemotherapy may be used to reduce the tumor burden before debulking surgery.

[0065] Soft Tissue Sarcomas: Neoadjuvant therapy is sometimes used to shrink and treat soft tissue sarcomas before surgery or radiation therapy.

[0066] The decision to use neoadjuvant therapy in these cases is based on the individual characteristics of the tumor, the stage of the cancer, and the overall health of the patient. It is employed as part of a comprehensive treatment strategy to improve the chances of successful treatment and longterm survival.

[0067] Endocrine therapy is a type of treatment used in the context of breast cancer, primarily for hormone receptor-positive breast cancer. Many breast cancers are influenced by hormones, specifically estrogen and progesterone. Tumors that have receptors for these hormones are called hormone receptor-positive breast cancers. In hormone receptor-positive breast cancer, these hormones can stimulate tumour growth and proliferation. Endocrine therapy in breast cancer aims to block or disrupt these hormonal signals to slow down or inhibit the growth of hormone receptor-positive breast tumors. Endocrine therapy includes, but is not limited to, the following drug types:

[0068] Selective Estrogen Receptor Modulators (SERMs): drugs that block the estrogen receptors on breast cancer cells. Tamoxifen is a well-known example of a SERM.

[0069] Aromatase Inhibitors: drugs that reduce the production of estrogen in the body. Als include medications like anastrozole, letrozole, and exemestane.

[0070] Luteinizing Hormone-Releasing Hormone (LHRH) Agonists are used in premenopausal women with hormone receptor-positive breast cancer. They work by reducing the production of ovarian hormones, such as estrogen and progesterone, which can affect the growth of breast cancer cells.

[0071] Selective Estrogen Receptor Degraders (SERDs): SERDs, like fulvestrant, degrade the estrogen receptors in cancer cells, leading to their destruction.

[0072] Medical treatment

[0073] Similarly, within the scope of the present invention is a method or treating cancer in a patient in need thereof, comprising administering to the patient a neoadjuvant cancer treatment according to the above description.

[0074] The invention further encompasses the use of nanomechanical profiling identified herein for use in the manufacture of a system enabling the prediction of outcome of neoadjuvant therapy in cancer, particularly in breast cancer.

[0075] Wherever alternatives for single separable features are laid out herein as “embodiments”, it is to be understood that such alternatives may be combined freely to form discrete embodiments of the invention disclosed herein.

[0076] 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.

[0077] Description of the Figures

[0078] Fig. 1 shows ARTIDIS Tissue measurements within routine clinical setting and translation into nanomechanical signature.;

[0079] Fig. 2 shows a cohort diagram of the study of the examples;

[0080] Fig. 3 shows a distribution of clinic-pathological characteristics of breast cancer (BC) patients among NAT responders and non-responders, RCR, radiological complete response, RPR*, radiological partial response, PCR, pathological complete response, PPR, pathological partial response. *Only one patient had radiological no-response and it has been calculated together with partial responders, rCR = radiological complete responders, rPR* = radiological partial responders (includes N = 1 rNR), rNR = radiological non responders, pCR = pathological complete responders, pPR = pathological partial responders;

[0081] Fig. 4 shows Radiological Response Threshold in the biphasic Stiffness / Dissipation Plane;

[0082] Fig. 5 shows Nanomechanical Signature differentiate responders from non-responders within the same histological grade, Panel A shows stiffness (left y-axis shows normalized density, right y-axis shows count as a function of the modulus backward and modulus forward (x-axis) in units of N / m2) and adhesion maps (left shows normalized density, right y-axis shows count as a function of the adhesion approximation in units of nN) in rNR patients, Panel B and C shows stiffness (modulus backward and modulus forward, axes as in Panel A), and adhesion (axes as in Panel A) rPR patients and Panel D shows stiffness (modulus backward and modulus forward, axes as in Panel A) and adhesion maps (axes as in Panel A) in rCR patients, Panel E (axes as in Panel A) shows the respective histopathological images of baseline biopsies, all patients are presented with stage II, G3 disease with no distinct histopathological features, Soft cell peak signature is reduced in responders independent of treatment, adhesion increases in responders independent of treatment, non responders or low responders exhibit heterogeneous stroma in both treatment groups;

[0083] Fig. 6 shows a distribution of pathological and radiological response in Basel NAT Cohort;

[0084] Figs. 7a, b show NAT response prediction by Nanomechanical Signature, ARTIDIS NS can predict the NAT pathological response with the sensitivity of 89% and specificity of 67%, PPV 89%, NPV 67% and accuracy 83% (AUC = 0.68);

[0085] Figs. 8a, b show NAT response prediction by NS with combination therapy and endocrine therapy, ARTIDIS NS predicts 95% of NAT response in all patients treated with both combination chemotherapy and endocrine therapy (AUC=0.91);

[0086] Fig. 9 shows NAT response prediction by NS for Complete Pathological Response;

[0087] Fig. 10a-d show from left to right Stiffness (left y-axis shows normalized density, right y-axis shows count as a function of the modulus backward (x-axis) in units of N / m2), Adhesion (left y-axis shows normalized density, right y-axis shows count as a function of the adhesion approximation in units of nN) and Histopathology Examples for Partial vs. Complete responders; and Fig. 11 shows a true positive rate ROC prediction of complete pathological response.

[0088] Examples

[0089] Example 1:

[0090] The inventors conducted a single center, blinded, prospective study to measure a multiparameter nanomechanical signature of response to neoadjuvant therapy in breast cancer. Between 2016 and 2019, 588 fresh, clinical breast biopsy samples from 545 patients were measured using the AFM based Automated and Reliable Tissue Diagnostics (ARTIDIS) investigational device - ART- 1 , within routine clinical setting in the Breast Clinic, University Hospital Basel. All patients who underwent clinically indicated breast biopsy and consented to participate, were eligible for the study. All biopsies were collected before treatment, and patients are being followed up to collect long term response up to 10 years. From our patient cohort, 35 patients received neoadjuvant therapy (NAT) including: anthracycline and / or taxane based chemo (n=17), anthracycline and / or taxane with platinum chemo (n=13) and endocrine NAT (n=5). Study endpoints were radiological complete response (rCR) prior and pathological complete response (pCR) after surgery. Nanomechanical signature data has been analyzed in an automated manner using proprietary ARTIDISNet software platform.

[0091] Patient and specimen characteristics

[0092] Total of 559 biopsy lesions were measured from 545 female patients undergoing clinically indicated VAB or CNB. A total of 25 patients and respective 29 lesions were excluded from analysis. In total 35 patients underwent neoadjuvant therapy after measurement of baseline biopsies. From these 35 patients, a total of 39 lesions were measured and analyzed. Detailed flow of patients is given in the cohort diagram shown in Figure 1.

[0093] Age distribution of study patients was between 25 and 86, with the mean age of 56y and median age of 52y. Patient BMI varied between 18.6 and 53.1 , with mean BMI of 28 and median BMI of 26.6. Out of 35 patients, 32 had single baseline biopsy measured by ARTIDIS, from which 9 / 32 had Her2+ BC, 2 / 32 patients had Luminal A BC, 11 / 32 patients had Luminal B BC, 5 / 32 patients had Luminal B-Like BC and 5 / 32 patients had TNBC. From 3 patients with two separate baseline biopsy measurement, molecular subtypes varied between biopsies: two patients were presented with Her2+ and TNBC disease, and one was presented with Her2+ and Luminal B disease. All these patients received combined neoadjuvant chemotherapy with anti-Her2 mAb treatment. In total, 5 / 35 patients received endocrine NAT and 30 patients received various combinations of chemotherapy and anti-Her2 mAb. In total 12 / 35 patients achieved radiological complete response (rCR), whilst only 9 / 35 patients achieved pathological complete response (pCR). Detailed cohort diagram is given in Figure 2 clinic-pathological characteristics of patients are given in Figure 3 and a summary in Figure 6. Results

[0094] The ARTIDIS nanomechanical signature of response to neoadjuvant therapy breast in cancer showed 100% negative predictive value (NPV) and 89% positive predictive value (PPV) with 93% of accuracy for patients receiving chemotherapy, independent of molecular subtype or treatment regimen. Sensitivity was 100% and specificity was 85% (AUC=0.91). When 5 patients with endocrine NAT were included, performance was slightly decreased, meaning: NPV=92%, PPV=91 , Sensitivity = 95 and Specificity = 85 (AUC=0.83) confirming that these should be analyzed as a separate group.

[0095] Nanomechanical signature of NAT responder and non-responder patients

[0096] From the multiparameter nanomechanical signature two major nanomechanical parameters have shown to differentiate NAT responders versus non-responders, including stiffness and adhesion; Figures 10a-d demonstrate the selected examples of nanomechanical profiles in patients with NAT partial and complete response, together with respective histopathological images.

[0097] Predictive value of Nanomechanical Signature

[0098] Our predictive modeling demonstrates that ARTIDIS NS can predict the NAT pathological response with the sensitivity of 89% and specificity of 67%, PPV 89%, NPV 67% and accuracy 83% (AUC = 0.68) (Figure 7a and Figure 7b).

[0099] Ourpredictive modeling demonstrated that ARTIDIS NS predicts 95% of NAT radiological response in all patients treated with both endocrine and combination chemotherapy (AUC=0.91). The sensitivity of the predictive test is 95%, specificity is 85%, Positive Predictive Value is 91 % and Negative predictive value is 92%. Test accuracy is 91% Figure 8a and Figure 8b). Whilst it predicts 100% of NAT radiological response in patients receiving chemotherapy (AUC=0.91 ). The sensitivity of ARTIDIS NS test is 100%, specificity is 85%, Positive Predictive Value is 89% and Negative Predictive Value is 100%, test accuracy = 93% (Figure 9).

[0100] Conclusion

[0101] We demonstrated that nanomechanical signature can be prospectively used in clinical settings to predict response to neoadjuvant therapy in breast cancer. Mechanistically, these results highlight the importance of cell and tumor microenvironment mechanics in modulating therapy response.

[0102] Discussion

[0103] Despite the substantial refinement of NAT modalities, by combining endocrine, targeted and more recently immune checkpoint inhibitor (ICPi) therapies with chemotherapy, response to NAT remains as low as 8 to 49% across different BC subtypes. To date, measurement of clinical, imaging, and biomarker changes at baseline (before treatment) have proven insufficient in predicting NAC response. Therefore, developing clinically useful assays to identify each intrinsic subtype, tumors that will respond well and improve risk stratification in patients with early-stage breast cancer has attracted considerable interest. Tumor initiation and progression is accompanied by complex biomechanical changes at sub- / cellular and extracellular levels. As mentioned above, cancer cells are substantially softer compared to their normal counterparts. This reflects the dysregulation of cellular signaling pathways, leading to increased deformability and motility of soft cancer cells to overcome stromal barrier, and spread into the adjacent tissues and distant sites in the body. On the other hand, tumor extracellular matrix (ECM) is characterized with high stiffness heterogeneity, caused by increased accumulation, and cross-linking of fibrous material, reflected as stromal desmoplasia during microscopic examination. It has been demonstrated that tumors with high desmoplasia are characterized with more aggressive behavior and poor survival outcomes. Tumors with high ECM stiffness show highly malignant phenotype, which is attributed to several reasons, including: the activation of cellular mechanosensing to promote directional cell migration and metastasis, direct mechanical modulation of chromatin, causing increased genomic instability, alteration of gene expression and intracellular signaling, remodeling of cytoskeleton and integrin signaling, leading to epithelial-mesenchymal transition accompanied by cancer cell migration and metastasis hampering the delivery of various systemic and targeted cancer therapeutics to cancer cells and causing mechanical pressure on tumour vasculature, creating hypoxic tumour microenvironment, which in turn is related to radiation, chemo- and targeted therapy resistance.

[0104] Atomic Force Microscopy (AFM) is the most reliable method to assess stiffness and overall mechanical properties of biological material at nanoscale resolution. The information of living cells, in particular, adhesion and stiffness, are believed being able to help to more accurately classify different kinds of cancer cells and to differentiate between cancer cells and benign cells. Furthermore, the mechanical properties of cells can be used to predict the location of metastases and can help to gain comprehensive understanding of the metastatic characteristics of cancer cells, which are of great significance for the diagnosis, analysis, and treatment of cancer cells.

[0105] To the best of our knowledge, we are first to demonstrate the NAT predictive value of multiparameter NS in a clinical setting. Such a predictive test has a significant clinical value, as NAT regimens are increasingly used in BC patients for the optimization of the extent of surgery and selection of adjuvant treatment modality based on NAT response. However, under- or overtreatment still represents a significant clinical problem, along with increased toxicities of new treatments. In addition, available clinicopathological parameters can only partially inform the treatment outcome and escalation or de-escalation strategies. Therefore, we aim to fill the urgent need of novel clinically valid biomarker for personalized BC care.

[0106] Material and methods

[0107] Patients

[0108] Study included altogether 545 patients undergoing core needle or vacuum-assisted breast biopsy at University Hospital Basel, Switzerland between April 2016 and May 2019. All female patients who showed suspicious breast lesions in a routine mammogram, breast ultrasound, breast MRI and / or clinical examination and who were going to have a breast biopsy were eligible to enroll upon signing the informed consent form. Patients younger than 18 years, necrotic and / or damaged biopsies and patients from which only one biopsy sample was taken were excluded from the study. Study did not influence the start of the patient's treatment and required no extra visits to the hospital. Study was approved by the ethics committee of Northwest and Central Switzerland (approval N.: EKNZ2015-171 , approved 28th of April, 2015). From 545 patients 35 patients received neoadjuvant therapy (NAT) after chemonaive biopsy investigation by ARTIDIS as a standard of care. From patients receiving NAT: 17 patients were treated with the anthracycline and / or taxane chemotherapy with or without anti-Her2 therapy as a first line NAT and 13 patients were treated with the combination of anthracycline and / or taxane with platinum based chemotherapy, with or without anti-Her2 treatment as a first line NAT, in addition 5 patients were treated with endocrine based NAT. Tumor biopsies prior to NAT and surgical specimens after NAT underwent a standard diagnostic assessment at the Department of Pathology, University Hospital Basel, Switzerland.

[0109] The major outcome of the study was NAT response, including the tumor regression measured by radiology according as following: Radiological Complete Response (rCR) - disappearance of all target lesions and decrease in size of pathological lymph nodes to <10mm short axis; Partial Response (rPR) - at least 30% decrease in sum of diameter of all target lesions from the sum of the diameters at baseline; No Response (rNR) no change in lesion or lymph node size or rather increase. Pathological response was defined as follows: Complete Response (pCR) - the absence of invasive carcinoma cells both in the breast and in the examined axillary lymph nodes; Partial Response (pPR) - presence of residual disease, as nodular, partially sclerotic, or as multiple foci within an edematous and / or sclerotic area; No-Response (pNR) - complete lack of pathological response. Long term clinical follow-up of patients is still ongoing, (detailed description of treatment regimens, types of surgery and other clinicopathological characteristics of patients with NAT are given in supplementary table 1).

[0110] Specimen characteristics

[0111] If the patient was willing to participate in the study and gave her written consent, one cylindrical biopsy with a diameter of ~ 1 .6 — 3 mm and length of 0.2-1 cm taken from a suspicious lesion was immediately transferred to ice-cold isotonic Custodiol (Essential Pharmaceuticals, LLC, Durham, NC, USA)) and kept at 4 °C to minimize tissue degradation. Prior to AFM measurement, the sample was attached to a substrate (sterile plastic culture dish bottom) to ensure solid contact during the entire measurement. For this purpose, two-component 5 min epoxy glue (Plodinec et. al, Nature Nanotechnology 7, 757-765 (2012)) was used. At all times, the specimen was maintained in the physiological Custodiol solution to prevent or minimize degradation. After measurement the specimen was stained with tissue marking inks to allow for correct spatial correlation of the NS and the post-measurement histology images. All biopsy specimens entered to standard histopathology diagnostic procedure after NS measurement. All specimens collected for this study were ex vivo biopsies acquired according to institutional and international standards. The decision for the biopsy procedure was not dependent on study participation. Hence, the study did not constitute any additional risks or side effects for the patients. The biopsy samples used for the study did not exhibit any histological alterations or damages that would disqualify them from the regular histopathological analysis performed after the AFM measurement.

[0112] Assay Methods

[0113] ARTIDIS nanomechanical measurements

[0114] Nanomechanical profiles were measured within 3.5 h after the biopsies were taken. The biopsy was horizontally aligned in the AFM top-view image to optimize exposure to the probe of the measuring surface. The first map was on the left side and the last map on the right side. The leftmost and the rightmost spots were defined, and 20 equidistant maps distributed within this selection (Plodinec et al., 2012a). In the presence of adipose tissue, areas classified by the optical detection as pure fat were avoided and the 20 maps were distributed homogeneously across the rest of the sample. One map consisted of 24 x 24 indentations over a 400 pm2surface area. The ramp length was not defined by the user but was optimized automatically by the software. The indentation speed was set to 16 pm / s. The 20 maps were measured within 3 h. If certain maps were deemed ‘poor quality’ by the software, the measurement was interrupted and a different map in the vicinity of the map measured (within 200 pm2). With each indentation, effective stiffness of local structures (e.g., extracellular matrix, cancer cells, etc.) that lie under the tip was measured.

[0115] Analysis of the Data

[0116] Data were stored and analyzed before the histological workup and before the diagnosis became available. With this temporal sequence, any user bias was unlikely. Technical measures within the AFM analysis software (‘Curve Quality Control’) were automated and user independent. For further minimization of the bias the study was double blinded, meaning data analysis team were not aware of clinical outcomes and clinical staff were not aware of AFM measurement outcomes. For the analysis of AFM force curves the method previously described by Plodinec et al., 2012 has been used. Briefly, the data was analyzed by LABVIEW software (National Instruments, USA) for the automated analysis of the force-volume data. The contact point was determined by applying a polynomial fit to raw force curves according to a published algorithm (Lin et al., 2007). Forceindentation data were obtained by the indentation h, which corresponds to the difference between piezo displacement and cantilever deflection, and by multiplying cantilever deflection d with the spring constant k to obtain load F. The slope of each data point is calculated by performing a linear fit to the upper 50% of the unloading force curve. The mean slope value from the Gaussian fit was then used for calculating elastic modulus (Es) for each cell type according to the Oliver and Pharr theory (Oliver and Pharr, 1992) applied by Loparic and coworkers (Stolz et al., 2004; Loparic et al., 2010).

[0117] Study Design

[0118] The study is monocentric, prospective, double blinded study was conducted on 545 patients to evaluate the potential of nanomechanical tissue profiling measured by atomic force microscopy based ARTIDIS (Automated and Reliable Tissue Diagnostics) technology as a physical biomarker for rapid BC diagnosis, prognosis, and prediction of treatment outcome. Patients who underwent NAT after biopsy were included in current study. Out of 35 patients assigned to NAT, 30 received chemotherapeutic regimens and 5 patients received endocrine therapy. Providing that all female patients who showed suspicious breast lesions in a routine mammogram, breast ultrasound, breast MRI and / or clinical examination and who were going to have a breast biopsy were eligible to enroll in the study during the period of 3 years (2016-2019), the sample size reflects the real word single center study data in Switzerland. ARTIDIS measurements were performed on the chemonaive biopsy and the tumor regression was determined by radiological imaging before and after NAT and by histopathological examination of post-surgical specimens. The end-points of the study were rCR and pCR. Long term clinical follow-up (10y) is currently ongoing.

[0119] Statistical methods

[0120] For each AFM parameter, we first aggregate the values from measurement to spot using different statistic aggregations, then aggregate again to the sample level. For example: dissipation_approximation_std_25% means first calculate the spot level standard deviation of dissipation_approximation, then calculate the 25% percentile of the spot std within the sample. Mean, median, 25 percentile, 75 percentile, standard deviation and IQR have been used for the aggregation. To narrow down to the most impactful features and improve the modelling performance, all features were passed into a random forest model to rank the feature impact using the random forest feature importance and top 2 features were selected for modelling and visualization. Random Forest Classifier on the selected top 2 features were used to separate Complete Responders vs Partial Responders. Leave-One-Out cross validation method was used to evaluate the performance and get the ROC curve. For each iteration, 1 sample is left out and a model is trained on the rest of the samples. The trained model was used to get a prediction on the left out sample until all samples get a prediction.

[0121] References

[0122] US2014007309A1 (METHOD FOR STAGING CANCER PROGRESSION BY AFM; Plodinec et al., to Uni Basel).

[0123] US2017299570A1 (Method for predicting cancer progression by nanomechanical profiling; Loparic et al.; to Uni Basel)

[0124] US2020253590A1 (CORE BIOPSY NEEDLE; Plodinec et al., to Uni Basel). US2015369838A1 (METHOD AND DEVICE FOR CONTROLLING A SCANNING PROBE MICROSCOPE; Lim et al. to Uni Basel).

[0125] All scientific publications and patent documents cited in the present specification are incorporated by reference herein.

Claims

Claims1 . A method to predict outcome of neoadjuvant therapy for a patient, comprising the steps of: subjecting a cancer tissue sample obtained from a patient ex-vivo to nanomechanical profiling to obtain a tissue stiffness nanomechanical signature; assigning to said patient a likelihood of being responsive to neoadjuvant therapy based on said nanomechanical signature.

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

3. The method according to claim 1 or 2, wherein the patient is a breast cancer patient.

4. The method according to any one of the preceding claims, wherein the patient is assigned a high likelihood of being a responder to neoadjuvant therapy.

5. The method according to claim 4, wherein the high likelihood of being a responder to neoadjuvant therapy is assigned based on the nanomechanical signature.

6. The method according to any one of the preceding claims, wherein the patient is assigned a high likelihood of being a responder to neoadjuvant endocrine therapy.

7. The method according to any one of the preceding claims, wherein the patient is assigned a high likelihood of being a responder to neoadjuvant chemotherapy.

8. The method according to claim 7, wherein the high likelihood of being a responder to neoadjuvant chemotherapy is assigned based on the nanomechanical signature.

9. The method according to claim 7 or 8, wherein the neoadjuvant chemotherapy comprises administration of a taxane.

10. The method according to claim 7 to 9, wherein the neoadjuvant chemotherapy comprises administration of an anthracycline drug.11 . The method according to any one of the preceding claims 7 to 10, wherein the neoadjuvant chemotherapy comprises administration further comprises administration of a Her-2 targeting drug.

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