Big data analysis uncovers major vulnerabilities in cancer

NEW YORK, NY (Jan 11, 2021) – Thousands of different gene mutations are implicated in cancer, but a new analysis of nearly 10,000 patients finds that regardless of the cancer’s origin, tumors can be divided into only 112 subtypes, within each Subtype, the major regulator proteins controlling carcinogenic transcriptional status were nearly identical, independent of specific patient-specific genetic mutations.

The study was published January 11 in prison cell, Confirms that key regulators provide molecular logic that integrates the effect of many different mutations and patient-specific mutations to implement the transcription state of a specific tumor subtype, thus greatly expanding the fraction of patients who may respond to the same treatment.

More specifically, rather than looking for drugs that target transgenes associated with increasingly smaller subsets of patients, the new study suggests that a much larger portion of patients may respond to new drug classes designed to target key regulator proteins.

The new analysis of thousands of tumors from all types of cancers also found that the key genetic programs needed for cancer cell survival are controlled mechanically by only 24 major regulatory units – called MR-blocks – each containing a few of these proteins. Work at the party.

The analysis, which has the potential to simplify and improve cancer treatment in the future, was led by Andrea Califano, Dr. Cory Abate Shane, Ph.D. Mariano Alvries, at the Vagilus College of Physicians and Surgeons at Columbia University and Herbert Irving Comprehensive Cancer Center.

“In personalized medicine today, we’re trying to determine which one from among the thousands of possible genetic mutations, or worse yet, the mutational patterns that may have caused an individual’s disease, and then hopefully have drugs that can target the activity of the relevant proteins,” says Califano, Clyde and Helen Wu Professor of Chemistry and Systems Biology and Chair of Systems Biology at Columbia University, Vagilus College of Physicians and Surgeons. “But rather than ordering drugs that target each different mutation, our study indicates that we may only need a few dozen different drugs that can target. MR blocks.

“Identifying a small number of active MR blocks in each individual’s cancer will guide us in choosing the most appropriate combination of drugs or drugs to treat them,” says Califano. This hypothesis is already being tested in a number of clinical trials, including breast cancer, pancreatic cancer, and neuroendocrine neoplasia, as well as in the Columbia Micro-tumor Initiative, a large-scale program aimed at assessing the value of genomics, immunotherapy, and Master Regulator-based therapies in 3,000 patients across eight types of severe tumors.

Personal therapy benefits a small number of people with cancer

Most cancer patients receive the same treatment that has been tested in thousands and thousands of patients. However, when these options fail, patients may choose a personalized approach, which includes identifying genetic mutations in a patient’s tumor to guide the choice of drugs that target those mutations.

Califano says that few patients actually benefit from this approach, because most tumors lack potentially treatable mutations, and few who have these mutations often fail to respond or relapse quickly after the initial response. “Relying only on identifying genetic mutations to guide personalized treatment hasn’t turned out to be a cool thing as we all hoped. Large-scale studies have shown that only 5% to 10% of patients benefit and that most eventually develop into a drug-resistant form of the tumor. Consequently, additional approaches are urgently needed. ” “For example, targeting the BRAF oncogene with inhibitors such as vemurafinib provides an unusual short-term response in melanoma patients with mutations in this gene. However, relapse occurs within a few months, so few overall benefits for survival are observed. have found “.

Califano and colleagues focused on a different approach to personalized therapy. Using methodologies based on advanced mathematics and physics to model complex biological systems, such as the molecular interactions that implement the biological logic of a cell, Califano and his team are gathering data from thousands of cancer samples to understand how genetic mutations affect the activity of all proteins in a malignant cell. In fact, genes are important only because they represent a blueprint for making proteins, while the latter are the molecules that preside over specific functions in the cell, including turning a normal cell into a tumor.

“If you model the cell as a complex electronic circuit, it becomes easy to identify the specific components in which the anomalous signals arising from the mutant genes converge,” he says. “Instead of individual mutations, these components represent the most global vulnerabilities of a cancer cell.”

Many of these meeting points are proteins that ultimately determine the fate of the cell, although they are rarely affected by mutations.

Califano calls these proteins, which are both necessary and sufficient to maintain cancer cells in nearly all types of cancer, their “prime regulators”. “You can think of PMOs as a narrow slot down the funnel,” he says. “The top of the funnel collects the effects of all relevant genetic mutations in the cell and” directs “it to that narrow slit.

“We think it would be more effective and efficient to simply deliver the end of the funnel, by targeting one or more of the key regulators, rather than targeting all of the mutant proteins that feed it.”

Main regulator blocks

Although key regulators were identified in several specific cancers, the new study looked for major regulators across 20 different types of cancer, as well as any overlap they might have across multiple types of cancer.

To achieve this goal, the Califano team developed a computational tool called Multi-Omics Master-Regulator Analysis (MOMA) to analyze gene expression and genetic modifications in tumors. They used MOMA to analyze 9,738 tissue samples from the National Cancer Institute Cancer Genome Atlas.

The analysis identified 407 key regulators across different types of cancer and found that they were organized into 24 unique and highly interconnected units, or master regulator blocks (MR-blocks). Each MR block contains a few key regulators who work in concert to control the hallmarks of cancer cell behavior. For example, MR-Block: 2, the most active cluster in most aggressive cancers, includes 14 regulators of cell growth, DNA repair, cell division, and cell proliferation. Activation of this cluster has been found to be predictive of poor outcomes in many different types of cancer. In contrast, MR-Block: 24 was found to be associated with inflammatory programs and immune response and thus was an indication of good outcomes in melanoma.

On average, between 2 to 6 MR blocks were activated in each individual tumor.

Targeting MR blocks as treatment

Califano’s team also showed that the MR-blocks activity in cell lines can be modified with drugs, which positively affects cell behavior in many types of cancer.

Targeting MR blocks, rather than individual mutated proteins, promises to prevent cancer cells from developing resistance, since individual MR blocks capture the influence of too many potential mutations in their primary pathways, which would inevitably lead to drug resistance.

“We have shown that if you target the MR blocks, it is very difficult for a cell to circumvent the blockade,” says Kalifano. “The cell will have to reprogram itself, which is something the cell does not like to do and often, albeit with some exceptions, of course, it leads to the death of the cell.”

Califano envisages that, in the future, each patient’s cancer may degrade into their own MR blocks and be treated with drugs designed to target them, either individually or in combination. The good news is that a tumor needs to be activated and deactivated abnormally many genetic programs to survive. Thus, even targeting only one of several MR-blocks is likely to lead to the demise of cancer cells, says Kalifano.

Unfortunately, although technology that easily identifies active MR blocks in a patient’s cancer already exists, few, if any, drugs have been specifically developed to target them. As a result, the Califano laboratory has developed algorithms to assess the ability of existing drugs to inhibit or activate individual MR blocks. For example, the study shows that four US Food and Drug Administration (FDA) approved experimental drugs already exist and are able to activate MR-Block: 14 in prostate cancer, which significantly reduces the cell’s ability to migrate and spread. Califano says drugs specifically designed to target key regulators should outpace existing drugs. As a result, a number of collaborations are underway to initiate the development of this new class of inhibitors despite the fact that, until very recently, the principal organizations considered proteins that were largely “non-disposable”.

“This is a new concept, so there has been very little development for such drugs,” says Califano. “But we’re already testing candidate drugs, and initial validation in both preclinical and clinical studies has greatly exceeded our expectations.”


more information

Andrea Califano is also the director of the GB Sulzberger Columbia Genome Center at Columbia University’s Irving Medical Center.

The study is entitled “A landscape of a standard principal regulator that determines the effect of genetic modifications on the transcriptional identity of cancer cells”.

Other contributors: Evan O. Paull (Columbia University), Alvaro Aytes (Columbia and Catalan Institute of Oncology, Bellvitge Institute for Biomedical Research, L’Hospitalet de Llobregat, Barcelona, ​​Spain), Sunny J. Jones (Columbia), Prem S. Subramaniam (Colombia), Federico M. Giorgi (University of Bologna, Italy), Eugene F. Douglas (Colombia), Somnath Tagore (Colombia), Brennan Chu (Colombia), Alessandro Vascavio (Colombia), Siwan Zeng (University of Texas MD) Center Anderson Cancer), Roel Fairhack (Jackson Genetic Medicine Laboratory), Corey Abate Shane (Colombia), and Mariano J. Alvarez (Darwin Health).

The research was funded by the US National Institutes of Health (R35-CA197745, U54-CA209997, U01-CA168426, R01-CA173481, R01-CA196662, S10-OD012351, and S10-OD0217640); Institute of Salud Carlos III / Ministry of Economic Affairs and Digital Transformation (Spain); And BBVA-Young Investigator Award Foundation.

The authors report the following conflicts of interest: Andrea Califano is the founder, stockholder, consultant, and director of DarwinHealth, a company that has licensed some of the algorithms used in this manuscript by Columbia University. Mariano J. Alvarez is the chief scientific officer and shareholder of DarwinHealth.

Columbia University’s Irving Medical Center provides international leadership in basic preclinical and clinical research. Teaching medical and health sciences. Take care of the sick. The Medical Center trains future leaders and includes the dedicated work of numerous physicians, scientists, public health professionals, dentists and nurses at the Vagilus College of Physicians and Surgeons, the Millman School of Public Health, the College of Dentistry and the College of Nursing, the biomedical departments of the Graduate School of Arts and Sciences, and allied research centers and institutions. The Columbia University Irving Medical Center is home to the largest medical research institution in the city and state of New York and one of the largest medical practices for faculty in the Northeast. For more information, visit or

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