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Prof. Arie Admon of the biology faculty claims that the test will provide doctors with a rich variety of information that until now has not been available and is suited to the trend of “personalized medicine,” in which treatment is suited to the genetic and other characteristics of the patient. The development was part of the doctoral work of Dr. Michal Bassani- Sternberg and will help suit medication to the patient.

As opposed to current blood tests for cancer which merely note whether cancerous cells are still in the blood stream, the new test will be able to differentiate between different kinds of cancers and tumors as well as other diseases. Scientists are now working on the technique.

Admon said it was known that when the proteins in a cell deteriorate or end their roles, they are broken down into their building blocks of amino acids to create new proteins. Some of the products of this process, however, are not completely broken down and remain as pieces of short proteins called peptides.

Meanwhile, some of these peptides are displayed on the surface of the cells with help from the human leukocyte antigen (HLA) protein. When the peptides from the proteins of the disease “report” their state of health to the immune system, the immune cells kill the sick cells and prevent the spread of the disease.

The body cells not only present the HLA protein on their surfaces but also release part of these protein molecules into the bloodstream with the characteristic peptides. Cancer cells release larger amounts of the HLA protein with the peptides into the blood in an effort to “confuse” the immune system, explained Admon. Thus, the two Technion researchers reached the conclusion that by characterizing the variety of peptides linked to the HLA proteins that were released into the blood, they could diagnose cancer and other disorders.

The researchers separated the HLA proteins from the other blood proteins and then released the linked peptides. Using a mass spectrometer device, they succeeded in identifying the sequence of amino acids of the separated peptides and the original proteins that were in the cells in which the peptides were produced.

In one blood sample, thousands of different peptides can be identified, providing vital information about the disease or the tumor. There are peptides that are not present in healthy people, and when they are found, the patient can be sent for additional tests, the researchers said.

Researchers at the Technion’s Ruth and Bruce Rappaport Faculty of Medicine and the Rap-paport Family Institute for Research in the Medical Sciences have discovered a subset of blood cells that predict the success of immunotherapy treatment. These findings are expected to streamline the process of matching an immunotherapy treatment to a specific patient, since it is

very important to identify in advance those patients who will react to a given treatment
The research published in Cancer Cell was led by doctoral student Madeleine Benguigui and post-doctoral fellow Dr. Tim J. Cooper, under the supervision of Professor Yuval Shaked of the Rappaport Faculty of Medicine. They contributed equally to the research and to the article. The translational research is based on RNA sequencing (scRNA-seq), analysis of existing data, pre-clinical models of cancer, and the corroboration of the findings in humans.
Background
Immunotherapy, which is considered one of the most important breakthroughs in the treatment of cancer, is based on the understanding that the natural immune system excels at attacking cancer cells in a selective and precise manner. The problem is that, in many cases, the cancer-ous tumor tricks the immune system and prevents it from identifying the cells as enemies. Im-munotherapy is based on the concept that, instead of attacking the cancer with chemotherapy drugs that also harm healthy tissue, it is preferable to boost the immune system with the goal to identify cancer cells as enemies and let it do the rest of the work on its own.
Despite the remarkable success of the immunotherapy approach for treating cancer, its effec-tiveness is still limited to around 40% of all patients. This means that many patients receive this harsh treatment without positive results. Consequently, it is crucial to attain a deep understanding of biological reactions to these treatments and to identify biomarkers that can predict the treat-ment’s future success.
Biomarkers are an important component of personalized medicine, which help physicians make educated medical decisions and formulate optimal treatment protocols adapted to the specific patient and their medical profile. Biomarkers are already being used for immunotherapy treat-ments, but they are obtained through biopsies – an invasive procedure that can endanger the patient. Moreover, this approach fails to sufficiently take into account the specific patient’s im-mune profile and its predictive capability is limited. For this reason, a great deal of research in this field – both in industry and in academia – strives to find new ways to predict which patients will respond to immunotherapy treatments.
The research itself
Technion researchers who focused on antibody-based immunotherapy discovered biomarkers that predict a specific patient’s response to the treatment. Since these biomarkers are in the bloodstream, they don’t require taking biopsies from the tumor – an invasive procedure that is not always feasible and, as mentioned, can sometimes endanger the patient.
In brief, the researchers discovered that a protein called STING, that activates the immune sys-tem, is triggered by cancerous growths, and is especially pronounced in cancer cells that will re-spond to immunotherapy treatment. This protein is manifested in interferon protein, which in turn stimulates neutrophils to be differentiated to a specific type (which expresses the protein Ly6Ehi). These neutrophils act directly on the immune system and stimulate it to target the cancerous tu-mor. Indeed, the researchers discovered that, these neutrophils may help the actual treatment, as their presence in the tumor prompts greater sensitivity to immunotherapy treatment.
The researchers inferred that testing the levels of Ly6Ehi neutrophils in the patient’s blood could serve as an efficient biomarker for predicting the response to immunotherapy treatment. The researchers tested these findings, which were based on pre-clinical studies, on patients with lung cancer and melanoma. These findings are consistent with the analysis of existing data on 1,237 cancer patients who underwent antibody-based immunotherapy treatments. Therefore, they demonstrated the neutrophils’ ability to predict with a high degree of precision, response to im-munotherapy in humans.
..
The technology developed by Prof. Yuval Shaked’s research group was registered as a patent and it is currently in the midst of a tech transfer process with the company OncoHost, in order to continue its development. Prof. Shaked points out that the technology can be used with the ubiq-uitous flow cytometry device, which can be found in almost every hospital and is approved by the regulatory agencies.
Various research groups from Israel and around the world took part in the research, including physicians and researchers from the Hadassah, Rambam, and Sheba Medical Centers, as well as from the University of Haifa, Heidelberg University (Germany), and Yale University (USA).
The research was supported by a European Research Council (ERC) grant, the Bruce & Ruth Rappaport Cancer Research Center, Israel Science Foundation, National Institutes of Health (USA), Ariane de Rothschild Foundation (Ariane de Rothschild Women’s Doctoral Program scholarship), and the Rappaport Technion Integrated Cancer Center (RTICC) as part of the Ste-ven & Beverly Rubenstein Charitable Foundation Fellowship Fund for Cancer Research.

Researchers at the Technion’s Ruth and Bruce Rappaport Faculty of Medicine and the Rappaport Family Institute for Research in the Medical Sciences have discovered a subset of blood cells that predict the success of immunotherapy treatment. These findings are expected to streamline the process of matching an immunotherapy treatment to a specific patient, since it is very important to identify in advance those patients who will react to a given treatment. The research published in Cancer Cell was led by doctoral student Madeleine Benguigui and post-doctoral fellow Dr. Tim J. Cooper, under the supervision of Professor Yuval Shaked of the Rappaport Faculty of Medicine. They contributed equally to the research and to the article. The translational research is based on RNA sequencing (scRNA-seq), analysis of existing data, pre-clinical models of cancer, and the corroboration of the findings in humans.

Background
Immunotherapy, which is considered one of the most important breakthroughs in the treatment of cancer, is based on the understanding that the natural immune system excels at attacking cancer cells in a selective and precise manner. The problem is that, in many cases, the cancerous tumor tricks the immune system and prevents it from identifying the cells as enemies. Immunotherapy is based on the concept that, instead of attacking the cancer with chemotherapy drugs that also harm healthy tissue, it is preferable to boost the immune system with the goal to identify cancer cells as enemies and let it do the rest of the work on its own. Despite the remarkable success of the immunotherapy approach for treating cancer, its effectiveness is still limited to around 40% of all patients. This means that many patients receive this harsh treatment without positive results. Consequently, it is crucial to attain a deep understanding of biological reactions to these treatments and to identify biomarkers that can predict the treatment’s future success.

Biomarkers are an important component of personalized medicine, which help physicians make educated medical decisions and formulate optimal treatment protocols adapted to the specific patient and their medical profile. Biomarkers are already being used for immunotherapy treat-ments, but they are obtained through biopsies – an invasive procedure that can endanger the patient. Moreover, this approach fails to sufficiently take into account the specific patient’s im-mune profile and its predictive capability is limited. For this reason, a great deal of research in this field – both in industry and in academia – strives to find new ways to predict which patients will respond to immunotherapy treatments.

The research itself
Technion researchers who focused on antibody-based immunotherapy discovered biomarkers that predict a specific patient’s response to the treatment. Since these biomarkers are in the bloodstream, they don’t require taking biopsies from the tumor – an invasive procedure that is not always feasible and, as mentioned, can sometimes endanger the patient.
In brief, the researchers discovered that a protein called STING, that activates the immune sys-tem, is triggered by cancerous growths, and is especially pronounced in cancer cells that will re-spond to immunotherapy treatment. This protein is manifested in interferon protein, which in turn stimulates neutrophils to be differentiated to a specific type (which expresses the protein Ly6Ehi). These neutrophils act directly on the immune system and stimulate it to target the cancerous tu-mor. Indeed, the researchers discovered that, these neutrophils may help the actual treatment, as their presence in the tumor prompts greater sensitivity to immunotherapy treatment. The researchers inferred that testing the levels of Ly6Ehi neutrophils in the patient’s blood could serve as an efficient biomarker for predicting the response to immunotherapy treatment. The researchers tested these findings, which were based on pre-clinical studies, on patients with lung cancer and melanoma. These findings are consistent with the analysis of existing data on 1,237 cancer patients who underwent antibody-based immunotherapy treatments. Therefore, they demonstrated the neutrophils’ ability to predict with a high degree of precision, response to immunotherapy in humans.

The technology developed by Prof. Yuval Shaked’s research group was registered as a patent and it is currently in the midst of a tech transfer process with the company OncoHost, in order to continue its development. Prof. Shaked points out that the technology can be used with the ubiquitous flow cytometry device, which can be found in almost every hospital and is approved by the regulatory agencies. Various research groups from Israel and around the world took part in the research, including physicians and researchers from the Hadassah, Rambam, and Sheba Medical Centers, as well as from the University of Haifa, Heidelberg University (Germany), and Yale University (USA). The research was supported by a European Research Council (ERC) grant, the Bruce & Ruth Rappaport Cancer Research Center, Israel Science Foundation, National Institutes of Health (USA), Ariane de Rothschild Foundation (Ariane de Rothschild Women’s Doctoral Program scholarship), and the Rappaport Technion Integrated Cancer Center (RTICC) as part of the Steven & Beverly Rubenstein Charitable Foundation Fellowship Fund for Cancer Research.

Four principal investigators from the Technion were recently awarded the ERC Starting Grant: Dr. Yonatan Belinkov from the Henry and Marilyn Taub Faculty of Computer Science, Dr. Yaniv Romano from the Henry and Marilyn Taub Faculty of Computer Science and the Andrew and Erna Viterbi Faculty of Electrical Engineering, Dr. Ari Glasner from the Ruth and Bruce Rappaport Faculty of Medicine, and Dr. Menahem (Hemi) Rotenberg from the Faculty of Biomedical Engineering. In 2024, the European Commission will fund 494 ERC Starting grants, with a success rate of 11%. The overall funding for these grants is €780 million.

Dr. Yonatan Belinkov was awarded the ERC for developing novel methods for elucidating the internal mechanisms of large language models (LLMs) to allow controlling LLMs in an efficient, interpretable, and safe manner. LLMs play a central role in many artificial intelligence (AI) systems, yet they operate like a black box – we do not understand their inner workings. The project aims to overcome the flaws of LLMs, such as biased behavior, out-of-date information, confabulations, flawed reasoning, and more.

Dr. Yaniv Romano was awarded the ERC for developing protective ecosystems that can be seamlessly plugged into any black-box machine learning (ML) model to monitor and guarantee its safety. Using statistical tools, Dr. Romano aims to put precise, interpretable, and robust error bounds on ML predictions, communicating what can be honestly inferred from data. In other words – he seeks to build trust in black-box predictions that affect people’s lives, opportunities, and science.

Dr. Ari Glasner from the Ruth and Bruce Rappaport Faculty of Medicine aims to better understand the interactions between the tumor microenvironment and immune cells. The project will comprehensively map interactions between stromal (connective, supporting tissue) cells and immune cells in the tissue microenvironment to elucidate the roles and programs carried out by each cell type. The findings will lay the foundations for identifying novel therapeutic candidates and strategies.

Dr. Hemi Rotenberg from the Faculty of Biomedical Engineering aims to develop an electro-mechanical bio-interface for neuronal tissue engineering. The interface will combine leadless electrical biomodulation induced via optical illumination of semiconducting silicon micro- and nanostructures, and mechanical perturbation using spatially defined iron microstructures manipulated via spatially homogenous magnetic fields. The new interface will allow researchers to apply electrical and/or mechanical modulation with high precision so that different parts of the same cell can be addressed simultaneously. This new tool has applications ranging from fundamental brain research to future translational clinical interventions.

Researchers at the Technion’s Ruth and Bruce Rappaport Faculty of Medicine and the Rappaport Family Institute for Research in the Medical Sciences have discovered a subset of blood cells that predict the success of immunotherapy treatment. These findings are expected to streamline the process of matching an immunotherapy treatment to a specific patient, since it is very important to identify in advance those patients who will react to a given treatment.

The research published in Cancer Cell was led by doctoral student Madeleine Benguigui and post-doctoral fellow Dr. Tim J. Cooper, under the supervision of Professor Yuval Shaked of the Rappaport Faculty of Medicine. They contributed equally to the research and to the article. The translational research is based on RNA sequencing (scRNA-seq), analysis of existing data, pre-clinical models of cancer, and the corroboration of the findings in humans.

Background

Immunotherapy, which is considered one of the most important breakthroughs in the treatment of cancer, is based on the understanding that the natural immune system excels at attacking cancer cells in a selective and precise manner. The problem is that, in many cases, the cancerous tumor tricks the immune system and prevents it from identifying the cells as enemies. Immunotherapy is based on the concept that, instead of attacking the cancer with chemotherapy drugs that also harm healthy tissue, it is preferable to boost the immune system with the goal to identify cancer cells as enemies and let it do the rest of the work on its own.

Despite the remarkable success of the immunotherapy approach for treating cancer, its effectiveness is still limited to around 40% of all patients. This means that many patients receive this harsh treatment without positive results. Consequently, it is crucial to attain a deep understanding of biological reactions to these treatments and to identify biomarkers that can predict the treatment’s future success.

Biomarkers are an important component of personalized medicine, which help physicians make educated medical decisions and formulate optimal treatment protocols adapted to the specific patient and their medical profile. Biomarkers are already being used for immunotherapy treatments, but they are obtained through biopsies – an invasive procedure that can endanger the patient. Moreover, this approach fails to sufficiently take into account the specific patient’s immune profile and its predictive capability is limited. For this reason, a great deal of research in this field – both in industry and in academia – strives to find new ways to predict which patients will respond to immunotherapy treatments.

The research itself

Technion researchers who focused on antibody-based immunotherapy discovered biomarkers that predict a specific patient’s response to the treatment. Since these biomarkers are in the bloodstream, they don’t require taking biopsies from the tumor – an invasive procedure that is not always feasible and, as mentioned, can sometimes endanger the patient.

In brief, the researchers discovered that a protein called STING, that activates the immune system, is triggered by cancerous growths, and is especially pronounced in cancer cells that will respond to immunotherapy treatment. This protein is manifested in interferon protein, which in turn stimulates neutrophils to be differentiated to a specific type (which expresses the protein Ly6E^hi). These neutrophils act directly on the immune system and stimulate it to target the cancerous tumor. Indeed, the researchers discovered that, these neutrophils may help the actual treatment, as their presence in the tumor prompts greater sensitivity to immunotherapy treatment.

The researchers inferred that testing the levels of Ly6E^hi neutrophils in the patient’s blood could serve as an efficient biomarker for predicting the response to immunotherapy treatment. The researchers tested these findings, which were based on pre-clinical studies, on patients with lung cancer and melanoma. These findings are consistent with the analysis of existing data on 1,237 cancer patients who underwent antibody-based immunotherapy treatments. Therefore, they demonstrated the neutrophils’ ability to predict with a high degree of precision, response to immunotherapy in humans.

The technology developed by Prof. Yuval Shaked’s research group was registered as a patent and it is currently in the midst of a tech transfer process with the company OncoHost, in order to continue its development. Prof. Shaked points out that the technology can be used with the ubiquitous flow cytometry device, which can be found in almost every hospital and is approved by the regulatory agencies.

Various research groups from Israel and around the world took part in the research, including physicians and researchers from the Hadassah, Rambam, and Sheba Medical Centers, as well as from the University of Haifa, Heidelberg University (Germany), and Yale University (USA).

The research was supported by a European Research Council (ERC) grant, the Bruce & Ruth Rappaport Cancer Research Center, Israel Science Foundation, National Institutes of Health (USA), Ariane de Rothschild Foundation (Ariane de Rothschild Women’s Doctoral Program scholarship), and the Rappaport Technion Integrated Cancer Center (RTICC) as part of the Steven & Beverly Rubenstein Charitable Foundation Fellowship Fund for Cancer Research.

Click here for the full article: https://www.cell.com/cancer-cell/pdf/S1535-6108(23)00433-6.pdf