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Archive for the ‘tumor microenvironment’ Category

Yet another Success Story: Machine Learning to predict immunotherapy response

Curator and Reporter: Dr. Premalata Pati, Ph.D., Postdoc

Immune-checkpoint blockers (ICBs) immunotherapy appears promising for various cancer types, offering a durable therapeutic advantage. Only a number of cases with cancer respond to this therapy. Biomarkers are required to adequately predict the responses of patients. This article evaluates this issue utilizing a system method to characterize the immune response of the anti-tumor based on the entire tumor environment. Researchers build mechanical biomarkers and cancer-specific response models using interpretable machine learning that predict the response of patients to ICB.

The lymphatic and immunological systems help the body defend itself by combating. The immune system functions as the body’s own personal police force, hunting down and eliminating pathogenic baddies.

According to Federica Eduati, Department of Biomedical Engineering at TU/e, “The immune system of the body is quite adept at detecting abnormally behaving cells. Cells that potentially grow into tumors or cancer in the future are included in this category. Once identified, the immune system attacks and destroys the cells.”

Immunotherapy and machine learning are combining to assist the immune system solve one of its most vexing problems: detecting hidden tumorous cells in the human body.

It is the fundamental responsibility of our immune system to identify and remove alien invaders like bacteria or viruses, but also to identify risks within the body, such as cancer. However, cancer cells have sophisticated ways of escaping death by shutting off immune cells. Immunotherapy can reverse the process, but not for all patients and types of cancer. To unravel the mystery, Eindhoven University of Technology researchers used machine learning. They developed a model to predict whether immunotherapy will be effective for a patient using a simple trick. Even better, the model outperforms conventional clinical approaches.

The outcomes of this research are published on 30th June, 2021 in the journal Patterns in an article entitled “Interpretable systems biomarkers predict response to immune-checkpoint inhibitors”.

The Study

  • Characterization of the tumor microenvironment from RNAseq and prior knowledge
  • Multi-task machine-learning models for predicting antitumor immune responses
  • Identification of cancer-type-specific, interpretable biomarkers of immune responses
  • EaSIeR is a tool to predict biomarker-based immunotherapy response from RNA-seq

“Tumor also contains multiple types of immune and fibroblast cells which can play a role in favor of or anti-tumor, and communicates among themselves,” said Oscar Lapuente-Santana, a researcher doctoral student in the computational biology group. “We had to learn how complicated regulatory mechanisms in the micro-environment of the tumor affect the ICB response. We have used RNA sequencing datasets to depict numerous components of the Tumor Microenvironment (TME) in a high-level illustration.”

Using computational algorithms and datasets from previous clinical patient care, the researchers investigated the TME.

Eduati explained

While RNA-sequencing databases are publically available, information on which patients responded to ICB therapy is only available for a limited group of patients and cancer types. So, to tackle the data problem, we used a trick.

All 100 models learned in the randomized cross-validation were included in the EaSIeR tool. For each validation dataset, we used the corresponding cancer-type-specific model: SKCM for the melanoma Gide, Auslander, Riaz, and Liu cohorts; STAD for the gastric cancer Kim cohort; BLCA for the bladder cancer Mariathasan cohort; and GBM for the glioblastoma Cloughesy cohort. To make predictions for each job, the average of the 100 cancer-type-specific models was employed. The predictions of each dataset’s cancer-type-specific models were also compared to models generated for the remaining 17 cancer types.

From the same datasets, the researchers selected several surrogate immunological responses to be used as a measure of ICB effectiveness.

Lapuente-Santana stated

One of the most difficult aspects of our job was properly training the machine learning models. We were able to fix this by looking at alternative immune responses during the training process.

Some of the researchers employed the machine learning approach given in the paper to participate in the “Anti-PD1 Response Prediction DREAM Challenge.”

DREAM is an organization that carries out crowd-based tasks with biomedical algorithms. “We were the first to compete in one of the sub-challenges under the name cSysImmunoOnco team,” Eduati remarks.

The researchers noted,

We applied machine learning to seek for connections between the obtained system-based attributes and the immune response, estimated using 14 predictors (proxies) derived from previous publications. We treated these proxies as individual tasks to be predicted by our machine learning models, and we employed multi-task learning algorithms to jointly learn all tasks.

The researchers discovered that their machine learning model surpasses biomarkers that are already utilized in clinical settings to evaluate ICB therapies.

But why are Eduati, Lapuente-Santana, and their colleagues using mathematical models to tackle a medical treatment problem? Is this going to take the place of the doctor?

Eduati explains

Mathematical models can provide an overview of the interconnection between individual molecules and cells and at the same time predicting a particular patient’s tumor behavior. This implies that immunotherapy with ICB can be personalized in a patient’s clinical setting. The models can aid physicians with their decisions about optimum therapy, it is vital to note that they will not replace them.

Furthermore, the model aids in determining which biological mechanisms are relevant for the biological response.

The researchers noted

Another advantage of our concept is that it does not need a dataset with known patient responses to immunotherapy for model training.

Further testing is required before these findings may be implemented in clinical settings.

Main Source:

Lapuente-Santana, Ó., van Genderen, M., Hilbers, P. A., Finotello, F., & Eduati, F. (2021). Interpretable systems biomarkers predict response to immune-checkpoint inhibitorsPatterns, 100293. https://www.cell.com/patterns/pdfExtended/S2666-3899(21)00126-4

Other Related Articles published in this Open Access Online Scientific Journal include the following:

Inhibitory CD161 receptor recognized as a potential immunotherapy target in glioma-infiltrating T cells by single-cell analysis

Reporter: Dr. Premalata Pati, Ph.D., Postdoc

https://pharmaceuticalintelligence.com/2021/02/20/inhibitory-cd161-receptor-identified-in-glioma-infiltrating-t-cells-by-single-cell-analysis-2/

Immunotherapy may help in glioblastoma survival

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

https://pharmaceuticalintelligence.com/2019/03/16/immunotherapy-may-help-in-glioblastoma-survival/

Deep Learning for In-silico Drug Discovery and Drug Repurposing: Artificial Intelligence to search for molecules boosting response rates in Cancer Immunotherapy: Insilico Medicine @John Hopkins University

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/07/17/deep-learning-for-in-silico-drug-discovery-and-drug-repurposing-artificial-intelligence-to-search-for-molecules-boosting-response-rates-in-cancer-immunotherapy-insilico-medicine-john-hopkins-univer/

Machine Learning (ML) in cancer prognosis prediction helps the researcher to identify multiple known as well as candidate cancer diver genes

Curator and Reporter: Dr. Premalata Pati, Ph.D., Postdoc

https://pharmaceuticalintelligence.com/2021/05/04/machine-learning-ml-in-cancer-prognosis-prediction-helps-the-researcher-to-identify-multiple-known-as-well-as-candidate-cancer-diver-genes/

AI System Used to Detect Lung Cancer

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2019/06/28/ai-system-used-to-detect-lung-cancer/

Cancer detection and therapeutics

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2016/05/02/cancer-detection-and-therapeutics/

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Renal tumor macrophages linked to recurrence are identified using single-cell protein activity analysis

Curator and Reporter: Dr. Premalata Pati, Ph.D., Postdoc

When malignancy returns after a period of remission, it is called a cancer recurrence. After the initial or primary cancer has been treated, this can happen weeks, months, or even years later. The possibility of recurrence is determined by the type of primary cancer. Because small patches of cancer cells might stay in the body after treatment, cancer might reoccur. These cells may multiply and develop large enough to cause symptoms or cause cancer over time. The type of cancer determines when and where cancer recurs. Some malignancies have a predictable recurrence pattern.

Even if primary cancer recurs in a different place of the body, recurrent cancer is designated for the area where it first appeared. If breast cancer recurs distantly in the liver, for example, it is still referred to as breast cancer rather than liver cancer. It’s referred to as metastatic breast cancer by doctors. Despite treatment, many people with kidney cancer eventually develop cancer recurrence and incurable metastatic illness.

The most frequent type of kidney cancer is Renal Cell Carcinoma (RCC). RCC is responsible for over 90% of all kidney malignancies. The appearance of cancer cells when viewed under a microscope helps to recognize the various forms of RCC. Knowing the RCC subtype can help the doctor assess if the cancer is caused by an inherited genetic condition and help to choose the best treatment option. The three most prevalent RCC subtypes are as follows:

  • Clear cell RCC
  • Papillary RCC
  • Chromophobe RCC

Clear Cell RCC (ccRCC) is the most prevalent subtype of RCC. The cells are clear or pale in appearance and are referred to as the clear cell or conventional RCC. Around 70% of people with renal cell cancer have ccRCC. The rate of growth of these cells might be sluggish or rapid. According to the American Society of Clinical Oncology (ASCO), clear cell RCC responds favorably to treatments like immunotherapy and treatments that target specific proteins or genes.

Researchers at Columbia University’s Vagelos College of Physicians and Surgeons have developed a novel method for identifying which patients are most likely to have cancer relapse following surgery.

The study

Their findings are detailed in a study published in the journal Cell entitled, “Single-Cell Protein Activity Analysis Identifies Recurrence-Associated Renal Tumor Macrophages.” The researchers show that the presence of a previously unknown type of immune cell in kidney tumors can predict who will have cancer recurrence.

According to co-senior author Charles Drake, MD, PhD, adjunct professor of medicine at Columbia University Vagelos College of Physicians and Surgeons and the Herbert Irving Comprehensive Cancer Center,

the findings imply that the existence of these cells could be used to identify individuals at high risk of disease recurrence following surgery who may be candidates for more aggressive therapy.

As Aleksandar Obradovic, an MD/PhD student at Columbia University Vagelos College of Physicians and Surgeons and the study’s co-first author, put it,

it’s like looking down over Manhattan and seeing that enormous numbers of people from all over travel into the city every morning. We need deeper details to understand how these different commuters engage with Manhattan residents: who are they, what do they enjoy, where do they go, and what are they doing?

To learn more about the immune cells that invade kidney cancers, the researchers employed single-cell RNA sequencing. Obradovic remarked,

In many investigations, single-cell RNA sequencing misses up to 90% of gene activity, a phenomenon known as gene dropout.

The researchers next tackled gene dropout by designing a prediction algorithm that can identify which genes are active based on the expression of other genes in the same family. “Even when a lot of data is absent owing to dropout, we have enough evidence to estimate the activity of the upstream regulator gene,” Obradovic explained. “It’s like when playing ‘Wheel of Fortune,’ because I can generally figure out what’s on the board even if most of the letters are missing.”

The meta-VIPER algorithm is based on the VIPER algorithm, which was developed in Andrea Califano’s group. Califano is the head of Herbert Irving Comprehensive Cancer Center’s JP Sulzberger Columbia Genome Center and the Clyde and Helen Wu professor of chemistry and systems biology. The researchers believe that by including meta-VIPER, they will be able to reliably detect the activity of 70% to 80% of all regulatory genes in each cell, eliminating cell-to-cell dropout.

Using these two methods, the researchers were able to examine 200,000 tumor cells and normal cells in surrounding tissues from eleven patients with ccRCC who underwent surgery at Columbia’s urology department.

The researchers discovered a unique subpopulation of immune cells that can only be found in tumors and is linked to disease relapse after initial treatment. The top genes that control the activity of these immune cells were discovered through the VIPER analysis. This “signature” was validated in the second set of patient data obtained through a collaboration with Vanderbilt University researchers; in this second set of over 150 patients, the signature strongly predicted recurrence.

These findings raise the intriguing possibility that these macrophages are not only markers of more risky disease, but may also be responsible for the disease’s recurrence and progression,” Obradovic said, adding that targeting these cells could improve clinical outcomes

Drake said,

Our research shows that when the two techniques are combined, they are extremely effective at characterizing cells within a tumor and in surrounding tissues, and they should have a wide range of applications, even beyond cancer research.

Main Source

Single-cell protein activity analysis identifies recurrence-associated renal tumor macrophages

https://www.cell.com/cell/fulltext/S0092-8674(21)00573-0

Other Related Articles published in this Open Access Online Scientific Journal include the following:

Machine Learning (ML) in cancer prognosis prediction helps the researcher to identify multiple known as well as candidate cancer diver genes

Curator and Reporter: Dr. Premalata Pati, Ph.D., Postdoc

https://pharmaceuticalintelligence.com/2021/05/04/machine-learning-ml-in-cancer-prognosis-prediction-helps-the-researcher-to-identify-multiple-known-as-well-as-candidate-cancer-diver-genes/

Renal (Kidney) Cancer: Connections in Metabolism at Krebs cycle  and Histone Modulation

Curator: Demet Sag, PhD, CRA, GCP

https://pharmaceuticalintelligence.com/2015/10/14/renal-kidney-cancer-connections-in-metabolism-at-krebs-cycle-through-histone-modulation/

Artificial Intelligence: Genomics & Cancer

https://pharmaceuticalintelligence.com/ai-in-genomics-cancer/

Bioinformatic Tools for Cancer Mutational Analysis: COSMIC and Beyond

Curator: Stephen J. Williams, Ph.D.

https://pharmaceuticalintelligence.com/2015/12/02/bioinformatic-tools-for-cancer-mutational-analysis-cosmic-and-beyond-2/

Deep-learning AI algorithm shines new light on mutations in once obscure areas of the genome

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2014/12/24/deep-learning-ai-algorithm-shines-new-light-on-mutations-in-once-obscure-areas-of-the-genome/

Premalata Pati, PhD, PostDoc in Biological Sciences, Medical Text Analysis with Machine Learning

https://pharmaceuticalintelligence.com/2021-medical-text-analysis-nlp/premalata-pati-phd-postdoc-in-pharmaceutical-sciences-medical-text-analysis-with-machine-learning/

Read Full Post »

Double Mutant PI3KA Found to Lead to Higher Oncogenic Signaling in Cancer Cells

Curator: Stephen J. Williams, PhD

PIK3CA (Phosphatidylinsitol 4,5-bisphosphate (PIP2) 3-kinase catalytic subunit α) is one of the most frequently mutated oncogenes in various tumor types ([1] and http://www.sanger.ac.uk/genetics/CGP/cosmic). Oncogenic mutations leading to the overactivation of PIK3CA, especially in context in of inactivating PTEN mutations, result in overtly high signaling activity and associated with the malignant phenotype.

In a Perspective article (Double trouble for cancer gene: Double mutations in an oncogene enhance tumor growth) in the journal Science[2], Dr. Alex Toker discusses the recent results of Vasan et al. in the same issue of Science[3] on the finding that double mutations in the same allele of PIK3CA are more frequent in cancer genomes than previously identified and these double mutations lead to increased PI3K pathway activation, increased tumor growth, and increased sensitivity to PI3K inhibitors in human breast cancer.

 

 

From Dr. Melvin Crasto blog NewDrugApprovals.org

Alpelisib: PIK3CA inhibitor:

Alpelisib: New PIK3CA inhibitor approved for HER2 negative metastatic breast cancer

 

FDA approves first PI3K inhibitor for breast cancer

syn https://newdrugapprovals.org/2018/06/25/alpelisib-byl-719/

Today, the U.S. Food and Drug Administration approved Piqray (alpelisib) tablets, to be used in combination with the FDA-approved endocrine therapy fulvestrant, to treat postmenopausal women, and men, with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative, PIK3CA-mutated, advanced or metastatic breast cancer (as detected by an FDA-approved test) following progression on or after an endocrine-based regimen.

The FDA also approved the companion diagnostic test, therascreen PIK3CA RGQ PCR Kit, to detect the PIK3CA mutation in a tissue and/or a liquid biopsy. Patients who are negative by

May 24, 2019

Today, the U.S. Food and Drug Administration approved Piqray (alpelisib) tablets, to be used in combination with the FDA-approved endocrine therapy fulvestrant, to treat postmenopausal women, and men, with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative, PIK3CA-mutated, advanced or metastatic breast cancer (as detected by an FDA-approved test) following progression on or after an endocrine-based regimen.

The FDA also approved the companion diagnostic test, therascreen PIK3CA RGQ PCR Kit, to detect the PIK3CA mutation in a tissue and/or a liquid biopsy. Patients who are negative by the therascreen test using the liquid biopsy should undergo tumor biopsy for PIK3CA mutation testing.

“Piqray is the first PI3K inhibitor to demonstrate a clinically meaningful benefit in treating patients with this type of breast cancer. The ability to target treatment to a patient’s specific genetic mutation or biomarker is becoming increasingly common in cancer treatment, and companion diagnostic tests assist oncologists in selecting patients who may benefit from these targeted treatments,” said Richard Pazdur, M.D., director of the FDA’s Oncology Center of Excellence and acting director of the Office of Hematology and Oncology Products in the FDA’s Center for Drug Evaluation and Research. “For this approval, we employed some of our newer regulatory tools to streamline reviews without compromising the quality of our assessment. This drug is the first novel drug approved under the Real-Time Oncology Review pilot program. We also used the updated Assessment Aid, a multidisciplinary review template that helps focus our written review on critical thinking and consistency and reduces time spent on administrative tasks.”

Metastatic breast cancer is breast cancer that has spread beyond the breast to other organs in the body (most often the bones, lungs, liver or brain). When breast cancer is hormone-receptor positive, patients may be treated with anti-hormonal treatment (also called endocrine therapy), alone or in combination with other medicines, or chemotherapy.

The efficacy of Piqray was studied in the SOLAR-1 trial, a randomized trial of 572 postmenopausal women and men with HR-positive, HER2-negative, advanced or metastatic breast cancer whose cancer had progressed while on or after receiving an aromatase inhibitor. Results from the trial showed the addition of Piqray to fulvestrant significantly prolonged progression- free survival (median of 11 months vs. 5.7 months) in patients whose tumors had a PIK3CA mutation.

Common side effects of Piqray are high blood sugar levels, increase in creatinine, diarrhea, rash, decrease in lymphocyte count in the blood, elevated liver enzymes, nausea, fatigue, low red blood cell count, increase in lipase (enzymes released by the pancreas), decreased appetite, stomatitis, vomiting, weight loss, low calcium levels, aPTT prolonged (blood clotting taking longer to occur than it should), and hair loss.

Health care professionals are advised to monitor patients taking Piqray for severe hypersensitivity reactions (intolerance). Patients are warned of potentially severe skin reactions (rashes that may result in peeling and blistering of skin or mucous membranes like the lips and gums). Health care professionals are advised not to initiate treatment in patients with a history of severe skin reactions such as Stevens-Johnson Syndrome, erythema multiforme, or toxic epidermal necrolysis. Patients on Piqray have reported severe hyperglycemia (high blood sugar), and the safety of Piqray in patients with Type 1 or uncontrolled Type 2 diabetes has not been established. Before initiating treatment with Piqray, health care professionals are advised to check fasting glucose and HbA1c, and to optimize glycemic control. Patients should be monitored for pneumonitis/interstitial lung disease (inflammation of lung tissue) and diarrhea during treatment. Piqray must be dispensed with a patient Medication Guide that describes important information about the drug’s uses and risks.

Piqray is the first new drug application (NDA) for a new molecular entity approved under the Real-Time Oncology Review (RTOR) pilot program, which permits the FDA to begin analyzing key efficacy and safety datasets prior to the official submission of an application, allowing the review team to begin their review and communicate with the applicant earlier. Piqray also used the updated Assessment Aid (AAid), a multidisciplinary review template intended to focus the FDA’s written review on critical thinking and consistency and reduce time spent on administrative tasks. With these two pilot programs, today’s approval of Piqray comes approximately three months ahead of the Prescription Drug User Fee Act (PDUFA) VI deadline of August 18, 2019.

The FDA granted this application Priority Review designation. The FDA granted approval of Piqray to Novartis. The FDA granted approval of the therascreen PIK3CA RGQ PCR Kit to QIAGEN Manchester, Ltd.

https://www.fda.gov/news-events/press-announcements/fda-approves-first-pi3k-inhibitor-breast-cancer?utm_campaign=052419_PR_FDA%20approves%20first%20PI3K%20inhibitor%20for%20breast%20cancer&utm_medium=email&utm_source=Eloqua

 

Alpelisib

(2S)-1-N-[4-methyl-5-[2-(1,1,1-trifluoro-2-methylpropan-2-yl)pyridin-4-yl]-1,3-thiazol-2-yl]pyrrolidine-1,2-dicarboxamide

PDT PAT WO 2010/029082

CHEMICAL NAMES: Alpelisib; CAS 1217486-61-7; BYL-719; BYL719; UNII-08W5N2C97Q; BYL 719
MOLECULAR FORMULA: C19H22F3N5O2S
MOLECULAR WEIGHT: 441.473 g/mol
  1. alpelisib
  2. 1217486-61-7
  3. BYL-719
  4. BYL719
  5. UNII-08W5N2C97Q
  6. BYL 719
  7. Alpelisib (BYL719)
  8. (S)-N1-(4-Methyl-5-(2-(1,1,1-trifluoro-2-methylpropan-2-yl)pyridin-4-yl)thiazol-2-yl)pyrrolidine-1,2-dicarboxamide
  9. NVP-BYL719

Alpelisib is an orally bioavailable phosphatidylinositol 3-kinase (PI3K) inhibitor with potential antineoplastic activity. Alpelisib specifically inhibits PI3K in the PI3K/AKT kinase (or protein kinase B) signaling pathway, thereby inhibiting the activation of the PI3K signaling pathway. This may result in inhibition of tumor cell growth and survival in susceptible tumor cell populations. Activation of the PI3K signaling pathway is frequently associated with tumorigenesis. Dysregulated PI3K signaling may contribute to tumor resistance to a variety of antineoplastic agents.

Alpelisib has been used in trials studying the treatment and basic science of Neoplasms, Solid Tumors, BREAST CANCER, 3rd Line GIST, and Rectal Cancer, among others.

 

SYN 2

POLYMORPHS

https://patents.google.com/patent/WO2012175522A1/en

(S)-pyrrolidine-l,2-dicarboxylic acid 2-amide l-(4-methyl-5-[2-(2,2,2-trifluoro-l,l- dimethyl-ethyl)-pyridin-4-yl]-thiazol-2-yl)-amidei hereafter referred to as compound I,

is an alpha-selective phosphatidylinositol 3 -kinase (PI3K) inhibitor. Compound I was originally described in WO 2010/029082, wherein the synthesis of its free base form was described. There is a need for additional solid forms of compound I, for use in drug substance and drug product development. It has been found that new solid forms of compound I can be prepared as one or more polymorph forms, including solvate forms. These polymorph forms exhibit new physical properties that may be exploited in order to obtain new pharmacological properties, and that may be utilized in drug substance and drug product development. Summary of the Invention

In one aspect, provided herein is a crystalline form of the compound of formula I, or a solvate of the crystalline form of the compound of formula I, or a salt of the crystalline form of the compound of formula I, or a solvate of a salt of the crystalline form of the compound of formula I. In one embodiment, the crystalline form of the compound of formula I has the polymorph form SA, SB, Sc, or SD.

In another aspect, provided herein is a pharmaceutical composition comprising a crystalline compound of formula I. In one embodiment of the pharmaceutical composition, the crystalline compound of formula I has the polymorph form SA, SB,Sc, or So.

In another aspect, provided herein is a method for the treatment of disorders mediated by PI3K, comprising administering to a patient in need of such treatment an effective amount of a crystalline compound of formula I, particularly SA, SB, SC,or SD .

In yet another aspect, provided herein is the use of a crystalline compound of formula I, particularly SA, SB, SC, or SD, for the preparation of a medicament for the treatment of disorders mediated by PI3K.

 

Source: https://newdrugapprovals.org/?s=alpelisib&submit=

 

Pharmacology and Toxicology from drugbank.ca

Indication

Alpelisib is indicated in combination with fulvestrant to treat postmenopausal women, and men, with advanced or metastatic breast cancer.Label This cancer must be hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative, and PIK3CA­ mutated.Label The cancer must be detected by an FDA-approved test following progression on or after an endocrine-based regimen.Label

Associated Conditions

Contraindications & Blackbox Warnings

Learn about our commercial Contraindications & Blackbox Warnings data.

LEARN MORE

 

Pharmacodynamics

Alpelisib does not prolong the QTcF interval.Label Patients taking alpelisib experience a dose dependent benefit from treatment with a 51% advantage of a 200mg daily dose over a 100mg dose and a 22% advantage of 300mg once daily over 150mg twice daily.6 This suggests patients requiring a lower dose may benefit from twice daily dosing.6

Mechanism of action

Phosphatidylinositol-3-kinase-α (PI3Kα) is responsible for cell proliferation in response to growth factor-tyrosine kinase pathway activation.3 In some cancers PI3Kα’s p110α catalytic subunit is mutated making it hyperactive.3 Alpelisib inhibits (PI3K), with the highest specificity for PI3Kα.Label

TARGET ACTIONS ORGANISM
APhosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform inhibitor Humans

Absorption

Alpelisib reached a peak concentration in plasma of 1320±912ng/mL after 2 hours.4 Alpelisib has an AUClast of 11,100±3760h ng/mL and an AUCINF of 11,100±3770h ng/mL.4 A large, high fat meal increases the AUC by 73% and Cmax by 84% while a small, low fat meal increases the AUC by 77% and Cmax by 145%.Label

Volume of distribution

The apparent volume of distribution at steady state is 114L.Label

Protein binding

Alpelisib is 89% protein bound.Label

Metabolism

Alpelisib is metabolized by hydrolysis reactions to form the primary metabolite.Label It is also metabolized by CYP3A4.Label The full metabolism of Alpelisib has yet to be determined but a series of reactions have been proposed.4,5 The main metabolic reaction is the substitution of an amine group on alpelisib for a hydroxyl group to form a metabolite known as M44,5 or BZG791.Label Alpelisib can also be glucuronidated to form the M1 and M12 metabolites.4,5

Hover over products below to view reaction partners

Route of elimination

36% of an oral dose is eliminated as unchanged drug in the feces and 32% as the primary metabolite BZG791 in the feces.Label 2% of an oral dose is eliminated in the urine as unchanged drug and 7.1% as the primary metabolite BZG791.Label In total 81% of an oral dose is eliminated in the feces and 14% is eliminated in the urine.Label

Half-life

The mean half life of alprelisib is 8 to 9 hours.Label

Clearance

The mean apparent oral clearance was 39.0L/h.4 The predicted clearance is 9.2L/hr under fed conditions.Label

Adverse Effects

Learn about our commercial Adverse Effects data.

LEARN MORE

 

Toxicity

LD50 and Overdose

Patients experiencing an overdose may present with hyperglycemia, nausea, asthenia, and rash.Label There is no antidote for an overdose of alpelisib so patients should be treated symptomatically.Label Data regarding an LD50 is not readily available.MSDS In clinical trials, patients were given doses of up to 450mg once daily.Label

Pregnancy, Lactation, and Fertility

Following administration in rats and rabbits during organogenesis, adverse effects on the reproductive system, such as embryo-fetal mortality, reduced fetal weights, and increased incidences of fetal malformations, were observed.Label Based on these findings of animals studies and its mechanism of action, it is proposed that alpelisib may cause embryo-fetal toxicity when administered to pregnant patients.Label There is no data available regarding the presence of alpelisib in breast milk so breast feeding mothers are advised not to breastfeed while taking this medication and for 1 week after their last dose.Label Based on animal studies, alpelisib may impair fertility of humans.Label

Carcinogenicity and Mutagenicity

Studies of carcinogenicity have yet to be performed.Label Alpelisib has not been found to be mutagenic in the Ames test.Label It is not aneugenic, clastogenic, or genotoxic in further assays.Label

Affected organisms

Not Available

Pathways

Not Available

Pharmacogenomic Effects/ADRs 

 

Not Available

 

Source: https://www.drugbank.ca/drugs/DB12015

References

  1. Yuan TL, Cantley LC: PI3K pathway alterations in cancer: variations on a theme. Oncogene 2008, 27(41):5497-5510.
  2. Toker A: Double trouble for cancer gene. Science 2019, 366(6466):685-686.
  3. Vasan N, Razavi P, Johnson JL, Shao H, Shah H, Antoine A, Ladewig E, Gorelick A, Lin TY, Toska E et al: Double PIK3CA mutations in cis increase oncogenicity and sensitivity to PI3Kalpha inhibitors. Science 2019, 366(6466):714-723.

 

 

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Live Notes, Real Time Conference Coverage AACR 2020: Tuesday June 23, 2020 3:00 PM-5:30 PM Educational Sessions

Reporter: Stephen J. Williams, PhD

Follow Live in Real Time using

#AACR20

@pharma_BI

@AACR

Register for FREE at https://www.aacr.org/

uesday, June 23

3:00 PM – 5:00 PM EDT

Virtual Educational Session
Tumor Biology, Bioinformatics and Systems Biology

The Clinical Proteomic Tumor Analysis Consortium: Resources and Data Dissemination

This session will provide information regarding methodologic and computational aspects of proteogenomic analysis of tumor samples, particularly in the context of clinical trials. Availability of comprehensive proteomic and matching genomic data for tumor samples characterized by the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) program will be described, including data access procedures and informatic tools under development. Recent advances on mass spectrometry-based targeted assays for inclusion in clinical trials will also be discussed.

Amanda G Paulovich, Shankha Satpathy, Meenakshi Anurag, Bing Zhang, Steven A Carr

Methods and tools for comprehensive proteogenomic characterization of bulk tumor to needle core biopsies

Shankha Satpathy
  • TCGA has 11,000 cancers with >20,000 somatic alterations but only 128 proteins as proteomics was still young field
  • CPTAC is NCI proteomic effort
  • Chemical labeling approach now method of choice for quantitative proteomics
  • Looked at ovarian and breast cancers: to measure PTM like phosphorylated the sample preparation is critical

 

Data access and informatics tools for proteogenomics analysis

Bing Zhang
  • Raw and processed data (raw MS data) with linked clinical data can be extracted in CPTAC
  • Python scripts are available for bioinformatic programming

 

Pathways to clinical translation of mass spectrometry-based assays

Meenakshi Anurag

·         Using kinase inhibitor pulldown (KIP) assay to identify unique kinome profiles

·         Found single strand break repair defects in endometrial luminal cases, especially with immune checkpoint prognostic tumors

·         Paper: JNCI 2019 analyzed 20,000 genes correlated with ET resistant in luminal B cases (selected for a list of 30 genes)

·         Validated in METABRIC dataset

·         KIP assay uses magnetic beads to pull out kinases to determine druggable kinases

·         Looked in xenografts and was able to pull out differential kinomes

·         Matched with PDX data so good clinical correlation

·         Were able to detect ESR1 fusion correlated with ER+ tumors

Tuesday, June 23

3:00 PM – 5:00 PM EDT

Virtual Educational Session
Survivorship

Artificial Intelligence and Machine Learning from Research to the Cancer Clinic

The adoption of omic technologies in the cancer clinic is giving rise to an increasing number of large-scale high-dimensional datasets recording multiple aspects of the disease. This creates the need for frameworks for translatable discovery and learning from such data. Like artificial intelligence (AI) and machine learning (ML) for the cancer lab, methods for the clinic need to (i) compare and integrate different data types; (ii) scale with data sizes; (iii) prove interpretable in terms of the known biology and batch effects underlying the data; and (iv) predict previously unknown experimentally verifiable mechanisms. Methods for the clinic, beyond the lab, also need to (v) produce accurate actionable recommendations; (vi) prove relevant to patient populations based upon small cohorts; and (vii) be validated in clinical trials. In this educational session we will present recent studies that demonstrate AI and ML translated to the cancer clinic, from prognosis and diagnosis to therapy.
NOTE: Dr. Fish’s talk is not eligible for CME credit to permit the free flow of information of the commercial interest employee participating.

Ron C. Anafi, Rick L. Stevens, Orly Alter, Guy Fish

Overview of AI approaches in cancer research and patient care

Rick L. Stevens
  • Deep learning is less likely to saturate as data increases
  • Deep learning attempts to learn multiple layers of information
  • The ultimate goal is prediction but this will be the greatest challenge for ML
  • ML models can integrate data validation and cross database validation
  • What limits the performance of cross validation is the internal noise of data (reproducibility)
  • Learning curves: not the more data but more reproducible data is important
  • Neural networks can outperform classical methods
  • Important to measure validation accuracy in training set. Class weighting can assist in development of data set for training set especially for unbalanced data sets

Discovering genome-scale predictors of survival and response to treatment with multi-tensor decompositions

Orly Alter
  • Finding patterns using SVD component analysis. Gene and SVD patterns match 1:1
  • Comparative spectral decompositions can be used for global datasets
  • Validation of CNV data using this strategy
  • Found Ras, Shh and Notch pathways with altered CNV in glioblastoma which correlated with prognosis
  • These predictors was significantly better than independent prognostic indicator like age of diagnosis

 

Identifying targets for cancer chronotherapy with unsupervised machine learning

Ron C. Anafi
  • Many clinicians have noticed that some patients do better when chemo is given at certain times of the day and felt there may be a circadian rhythm or chronotherapeutic effect with respect to side effects or with outcomes
  • ML used to determine if there is indeed this chronotherapy effect or can we use unstructured data to determine molecular rhythms?
  • Found a circadian transcription in human lung
  • Most dataset in cancer from one clinical trial so there might need to be more trials conducted to take into consideration circadian rhythms

Stratifying patients by live-cell biomarkers with random-forest decision trees

Stratifying patients by live-cell biomarkers with random-forest decision trees

Guy Fish CEO Cellanyx Diagnostics

 

Tuesday, June 23

3:00 PM – 5:00 PM EDT

Virtual Educational Session
Tumor Biology, Molecular and Cellular Biology/Genetics, Bioinformatics and Systems Biology, Prevention Research

The Wound Healing that Never Heals: The Tumor Microenvironment (TME) in Cancer Progression

This educational session focuses on the chronic wound healing, fibrosis, and cancer “triad.” It emphasizes the similarities and differences seen in these conditions and attempts to clarify why sustained fibrosis commonly supports tumorigenesis. Importance will be placed on cancer-associated fibroblasts (CAFs), vascularity, extracellular matrix (ECM), and chronic conditions like aging. Dr. Dvorak will provide an historical insight into the triad field focusing on the importance of vascular permeability. Dr. Stewart will explain how chronic inflammatory conditions, such as the aging tumor microenvironment (TME), drive cancer progression. The session will close with a review by Dr. Cukierman of the roles that CAFs and self-produced ECMs play in enabling the signaling reciprocity observed between fibrosis and cancer in solid epithelial cancers, such as pancreatic ductal adenocarcinoma.

Harold F Dvorak, Sheila A Stewart, Edna Cukierman

 

The importance of vascular permeability in tumor stroma generation and wound healing

Harold F Dvorak

Aging in the driver’s seat: Tumor progression and beyond

Sheila A Stewart

Why won’t CAFs stay normal?

Edna Cukierman

 

Tuesday, June 23

3:00 PM – 5:00 PM EDT

 

 

 

 

 

 

 

Other Articles on this Open Access  Online Journal on Cancer Conferences and Conference Coverage in Real Time Include

Press Coverage
Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 PM
Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on NCI Activities: COVID-19 and Cancer Research 5:20 PM
Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM
Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Novel Targets and Therapies 2:35 PM

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Live Notes, Real Time Conference Coverage AACR 2020 #AACR20: Tuesday June 23, 2020 Noon-2:45 Educational Sessions

Live Notes, Real Time Conference Coverage AACR 2020: Tuesday June 23, 2020 Noon-2:45 Educational Sessions

Reporter: Stephen J. Williams, PhD

Follow Live in Real Time using

#AACR20

@pharma_BI

@AACR

Register for FREE at https://www.aacr.org/

 

Presidential Address

Elaine R Mardis, William N Hait

DETAILS

Welcome and introduction

William N Hait

 

Improving diagnostic yield in pediatric cancer precision medicine

Elaine R Mardis
  • Advent of genomics have revolutionized how we diagnose and treat lung cancer
  • We are currently needing to understand the driver mutations and variants where we can personalize therapy
  • PD-L1 and other checkpoint therapy have not really been used in pediatric cancers even though CAR-T have been successful
  • The incidence rates and mortality rates of pediatric cancers are rising
  • Large scale study of over 700 pediatric cancers show cancers driven by epigenetic drivers or fusion proteins. Need for transcriptomics.  Also study demonstrated that we have underestimated germ line mutations and hereditary factors.
  • They put together a database to nominate patients on their IGM Cancer protocol. Involves genetic counseling and obtaining germ line samples to determine hereditary factors.  RNA and protein are evaluated as well as exome sequencing. RNASeq and Archer Dx test to identify driver fusions
  • PECAN curated database from St. Jude used to determine driver mutations. They use multiple databases and overlap within these databases and knowledge base to determine or weed out false positives
  • They have used these studies to understand the immune infiltrate into recurrent cancers (CytoCure)
  • They found 40 germline cancer predisposition genes, 47 driver somatic fusion proteins, 81 potential actionable targets, 106 CNV, 196 meaningful somatic driver mutations

 

 

Tuesday, June 23

12:00 PM – 12:30 PM EDT

Awards and Lectures

NCI Director’s Address

Norman E Sharpless, Elaine R Mardis

DETAILS

Introduction: Elaine Mardis

 

NCI Director Address: Norman E Sharpless
  • They are functioning well at NCI with respect to grant reviews, research, and general functions in spite of the COVID pandemic and the massive demonstrations on also focusing on the disparities which occur in cancer research field and cancer care
  • There are ongoing efforts at NCI to make a positive difference in racial injustice, diversity in the cancer workforce, and for patients as well
  • Need a diverse workforce across the cancer research and care spectrum
  • Data show that areas where the clinicians are successful in putting African Americans on clinical trials are areas (geographic and site specific) where health disparities are narrowing
  • Grants through NCI new SeroNet for COVID-19 serologic testing funded by two RFAs through NIAD (RFA-CA-30-038 and RFA-CA-20-039) and will close on July 22, 2020

 

Tuesday, June 23

12:45 PM – 1:46 PM EDT

Virtual Educational Session

Immunology, Tumor Biology, Experimental and Molecular Therapeutics, Molecular and Cellular Biology/Genetics

Tumor Immunology and Immunotherapy for Nonimmunologists: Innovation and Discovery in Immune-Oncology

This educational session will update cancer researchers and clinicians about the latest developments in the detailed understanding of the types and roles of immune cells in tumors. It will summarize current knowledge about the types of T cells, natural killer cells, B cells, and myeloid cells in tumors and discuss current knowledge about the roles these cells play in the antitumor immune response. The session will feature some of the most promising up-and-coming cancer immunologists who will inform about their latest strategies to harness the immune system to promote more effective therapies.

Judith A Varner, Yuliya Pylayeva-Gupta

 

Introduction

Judith A Varner
New techniques reveal critical roles of myeloid cells in tumor development and progression
  • Different type of cells are becoming targets for immune checkpoint like myeloid cells
  • In T cell excluded or desert tumors T cells are held at periphery so myeloid cells can infiltrate though so macrophages might be effective in these immune t cell naïve tumors, macrophages are most abundant types of immune cells in tumors
  • CXCLs are potential targets
  • PI3K delta inhibitors,
  • Reduce the infiltrate of myeloid tumor suppressor cells like macrophages
  • When should we give myeloid or T cell therapy is the issue
Judith A Varner
Novel strategies to harness T-cell biology for cancer therapy
Positive and negative roles of B cells in cancer
Yuliya Pylayeva-Gupta
New approaches in cancer immunotherapy: Programming bacteria to induce systemic antitumor immunity

 

 

Tuesday, June 23

12:45 PM – 1:46 PM EDT

Virtual Educational Session

Cancer Chemistry

Chemistry to the Clinic: Part 2: Irreversible Inhibitors as Potential Anticancer Agents

There are numerous examples of highly successful covalent drugs such as aspirin and penicillin that have been in use for a long period of time. Despite historical success, there was a period of reluctance among many to purse covalent drugs based on concerns about toxicity. With advances in understanding features of a well-designed covalent drug, new techniques to discover and characterize covalent inhibitors, and clinical success of new covalent cancer drugs in recent years, there is renewed interest in covalent compounds. This session will provide a broad look at covalent probe compounds and drug development, including a historical perspective, examination of warheads and electrophilic amino acids, the role of chemoproteomics, and case studies.

Benjamin F Cravatt, Richard A. Ward, Sara J Buhrlage

 

Discovering and optimizing covalent small-molecule ligands by chemical proteomics

Benjamin F Cravatt
  • Multiple approaches are being investigated to find new covalent inhibitors such as: 1) cysteine reactivity mapping, 2) mapping cysteine ligandability, 3) and functional screening in phenotypic assays for electrophilic compounds
  • Using fluorescent activity probes in proteomic screens; have broad useability in the proteome but can be specific
  • They screened quiescent versus stimulated T cells to determine reactive cysteines in a phenotypic screen and analyzed by MS proteomics (cysteine reactivity profiling); can quantitate 15000 to 20,000 reactive cysteines
  • Isocitrate dehydrogenase 1 and adapter protein LCP-1 are two examples of changes in reactive cysteines they have seen using this method
  • They use scout molecules to target ligands or proteins with reactive cysteines
  • For phenotypic screens they first use a cytotoxic assay to screen out toxic compounds which just kill cells without causing T cell activation (like IL10 secretion)
  • INTERESTINGLY coupling these MS reactive cysteine screens with phenotypic screens you can find NONCANONICAL mechanisms of many of these target proteins (many of the compounds found targets which were not predicted or known)

Electrophilic warheads and nucleophilic amino acids: A chemical and computational perspective on covalent modifier

The covalent targeting of cysteine residues in drug discovery and its application to the discovery of Osimertinib

Richard A. Ward
  • Cysteine activation: thiolate form of cysteine is a strong nucleophile
  • Thiolate form preferred in polar environment
  • Activation can be assisted by neighboring residues; pKA will have an effect on deprotonation
  • pKas of cysteine vary in EGFR
  • cysteine that are too reactive give toxicity while not reactive enough are ineffective

 

Accelerating drug discovery with lysine-targeted covalent probes

 

Tuesday, June 23

12:45 PM – 2:15 PM EDT

Virtual Educational Session

Molecular and Cellular Biology/Genetics

Virtual Educational Session

Tumor Biology, Immunology

Metabolism and Tumor Microenvironment

This Educational Session aims to guide discussion on the heterogeneous cells and metabolism in the tumor microenvironment. It is now clear that the diversity of cells in tumors each require distinct metabolic programs to survive and proliferate. Tumors, however, are genetically programmed for high rates of metabolism and can present a metabolically hostile environment in which nutrient competition and hypoxia can limit antitumor immunity.

Jeffrey C Rathmell, Lydia Lynch, Mara H Sherman, Greg M Delgoffe

 

T-cell metabolism and metabolic reprogramming antitumor immunity

Jeffrey C Rathmell

Introduction

Jeffrey C Rathmell

Metabolic functions of cancer-associated fibroblasts

Mara H Sherman

Tumor microenvironment metabolism and its effects on antitumor immunity and immunotherapeutic response

Greg M Delgoffe
  • Multiple metabolites, reactive oxygen species within the tumor microenvironment; is there heterogeneity within the TME metabolome which can predict their ability to be immunosensitive
  • Took melanoma cells and looked at metabolism using Seahorse (glycolysis): and there was vast heterogeneity in melanoma tumor cells; some just do oxphos and no glycolytic metabolism (inverse Warburg)
  • As they profiled whole tumors they could separate out the metabolism of each cell type within the tumor and could look at T cells versus stromal CAFs or tumor cells and characterized cells as indolent or metabolic
  • T cells from hyerglycolytic tumors were fine but from high glycolysis the T cells were more indolent
  • When knock down glucose transporter the cells become more glycolytic
  • If patient had high oxidative metabolism had low PDL1 sensitivity
  • Showed this result in head and neck cancer as well
  • Metformin a complex 1 inhibitor which is not as toxic as most mito oxphos inhibitors the T cells have less hypoxia and can remodel the TME and stimulate the immune response
  • Metformin now in clinical trials
  • T cells though seem metabolically restricted; T cells that infiltrate tumors are low mitochondrial phosph cells
  • T cells from tumors have defective mitochondria or little respiratory capacity
  • They have some preliminary findings that metabolic inhibitors may help with CAR-T therapy

Obesity, lipids and suppression of anti-tumor immunity

Lydia Lynch
  • Hypothesis: obesity causes issues with anti tumor immunity
  • Less NK cells in obese people; also produce less IFN gamma
  • RNASeq on NOD mice; granzymes and perforins at top of list of obese downregulated
  • Upregulated genes that were upregulated involved in lipid metabolism
  • All were PPAR target genes
  • NK cells from obese patients takes up palmitate and this reduces their glycolysis but OXPHOS also reduced; they think increased FFA basically overloads mitochondria
  • PPAR alpha gamma activation mimics obesity

 

 

Tuesday, June 23

12:45 PM – 2:45 PM EDT

Virtual Educational Session

Clinical Research Excluding Trials

The Evolving Role of the Pathologist in Cancer Research

Long recognized for their role in cancer diagnosis and prognostication, pathologists are beginning to leverage a variety of digital imaging technologies and computational tools to improve both clinical practice and cancer research. Remarkably, the emergence of artificial intelligence (AI) and machine learning algorithms for analyzing pathology specimens is poised to not only augment the resolution and accuracy of clinical diagnosis, but also fundamentally transform the role of the pathologist in cancer science and precision oncology. This session will discuss what pathologists are currently able to achieve with these new technologies, present their challenges and barriers, and overview their future possibilities in cancer diagnosis and research. The session will also include discussions of what is practical and doable in the clinic for diagnostic and clinical oncology in comparison to technologies and approaches primarily utilized to accelerate cancer research.

 

Jorge S Reis-Filho, Thomas J Fuchs, David L Rimm, Jayanta Debnath

DETAILS

Tuesday, June 23

12:45 PM – 2:45 PM EDT

 

High-dimensional imaging technologies in cancer research

David L Rimm

  • Using old methods and new methods; so cell counting you use to find the cells then phenotype; with quantification like with Aqua use densitometry of positive signal to determine a threshold to determine presence of a cell for counting
  • Hiplex versus multiplex imaging where you have ten channels to measure by cycling of flour on antibody (can get up to 20plex)
  • Hiplex can be coupled with Mass spectrometry (Imaging Mass spectrometry, based on heavy metal tags on mAbs)
  • However it will still take a trained pathologist to define regions of interest or field of desired view

 

Introduction

Jayanta Debnath

Challenges and barriers of implementing AI tools for cancer diagnostics

Jorge S Reis-Filho

Implementing robust digital pathology workflows into clinical practice and cancer research

Jayanta Debnath

Invited Speaker

Thomas J Fuchs
  • Founder of spinout of Memorial Sloan Kettering
  • Separates AI from computational algothimic
  • Dealing with not just machines but integrating human intelligence
  • Making decision for the patients must involve human decision making as well
  • How do we get experts to do these decisions faster
  • AI in pathology: what is difficult? =è sandbox scenarios where machines are great,; curated datasets; human decision support systems or maps; or try to predict nature
  • 1) learn rules made by humans; human to human scenario 2)constrained nature 3)unconstrained nature like images and or behavior 4) predict nature response to nature response to itself
  • In sandbox scenario the rules are set in stone and machines are great like chess playing
  • In second scenario can train computer to predict what a human would predict
  • So third scenario is like driving cars
  • System on constrained nature or constrained dataset will take a long time for commuter to get to decision
  • Fourth category is long term data collection project
  • He is finding it is still finding it is still is difficult to predict nature so going from clinical finding to prognosis still does not have good predictability with AI alone; need for human involvement
  • End to end partnering (EPL) is a new way where humans can get more involved with the algorithm and assist with the problem of constrained data
  • An example of a workflow for pathology would be as follows from Campanella et al 2019 Nature Medicine: obtain digital images (they digitized a million slides), train a massive data set with highthroughput computing (needed a lot of time and big software developing effort), and then train it using input be the best expert pathologists (nature to human and unconstrained because no data curation done)
  • Led to first clinically grade machine learning system (Camelyon16 was the challenge for detecting metastatic cells in lymph tissue; tested on 12,000 patients from 45 countries)
  • The first big hurdle was moving from manually annotated slides (which was a big bottleneck) to automatically extracted data from path reports).
  • Now problem is in prediction: How can we bridge the gap from predicting humans to predicting nature?
  • With an AI system pathologist drastically improved the ability to detect very small lesions

 

Virtual Educational Session

Epidemiology

Cancer Increases in Younger Populations: Where Are They Coming from?

Incidence rates of several cancers (e.g., colorectal, pancreatic, and breast cancers) are rising in younger populations, which contrasts with either declining or more slowly rising incidence in older populations. Early-onset cancers are also more aggressive and have different tumor characteristics than those in older populations. Evidence on risk factors and contributors to early-onset cancers is emerging. In this Educational Session, the trends and burden, potential causes, risk factors, and tumor characteristics of early-onset cancers will be covered. Presenters will focus on colorectal and breast cancer, which are among the most common causes of cancer deaths in younger people. Potential mechanisms of early-onset cancers and racial/ethnic differences will also be discussed.

Stacey A. Fedewa, Xavier Llor, Pepper Jo Schedin, Yin Cao

Cancers that are and are not increasing in younger populations

Stacey A. Fedewa

 

  • Early onset cancers, pediatric cancers and colon cancers are increasing in younger adults
  • Younger people are more likely to be uninsured and these are there most productive years so it is a horrible life event for a young adult to be diagnosed with cancer. They will have more financial hardship and most (70%) of the young adults with cancer have had financial difficulties.  It is very hard for women as they are on their childbearing years so additional stress
  • Types of early onset cancer varies by age as well as geographic locations. For example in 20s thyroid cancer is more common but in 30s it is breast cancer.  Colorectal and testicular most common in US.
  • SCC is decreasing by adenocarcinoma of the cervix is increasing in women’s 40s, potentially due to changing sexual behaviors
  • Breast cancer is increasing in younger women: maybe etiologic distinct like triple negative and larger racial disparities in younger African American women
  • Increased obesity among younger people is becoming a factor in this increasing incidence of early onset cancers

 

 

Other Articles on this Open Access  Online Journal on Cancer Conferences and Conference Coverage in Real Time Include

Press Coverage

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on NCI Activities: COVID-19 and Cancer Research 5:20 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Novel Targets and Therapies 2:35 PM

 

Read Full Post »

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 27, 2020 Minisymposium on Drugging Undrugged Cancer Targets 1:30 pm – 5:00 pm

SESSION VMS.ET01.01 – Drugging Undrugged Cancer Targets

April 27, 2020, 1:30 PM – 3:30 PM
Virtual Meeting: All Session Times Are U.S. EDT

Session Type
Virtual Minisymposium
Track(s)
Experimental and Molecular Therapeutics,Drug Development
18 Presentations
1:30 PM – 1:30 PM
– ChairpersonPeter C. Lucas. University of Pittsburgh School of Medicine, Pittsburgh, PA

1:30 PM – 1:30 PM
– ChairpersonJohn S. Lazo. University of Virginia, Charlottesville, VA

1:30 PM – 1:35 PM
– IntroductionPeter C. Lucas. University of Pittsburgh School of Medicine, Pittsburgh, PA

1:35 PM – 1:45 PM
3398 – PTPN22 is a systemic target for augmenting antitumor immunityWon Jin Ho, Jianping Lin, Ludmila Danilova, Zaw Phyo, Soren Charmsaz, Aditya Mohan, Todd Armstrong, Ben H. Park, Elana J. Fertig, Zhong-Yin Zhang, Elizabeth M. Jaffee. Johns Hopkins Sidney Kimmel Comp. Cancer Center, Baltimore, MD, Purdue University, Baltimore, MD, Johns Hopkins Sidney Kimmel Comp. Cancer Center, Baltimore, MD, Vanderbilt University Medical Center, Baltimore, MD

Abstract: Remarkable progress in cancer immunology has revolutionized cancer therapy. The majority of patients, however, do not respond to immunotherapeutic options, warranting the ongoing search for better strategies. Leveraging the established role of protein tyrosine phosphatase non-receptor type 22 (PTPN22) in autoimmune diseases, we hypothesized that PTPN22 is a novel target for cancer immunotherapy. PTPN22 is a physiologic regulator of T cell receptor (TCR) signaling acting by dephosphorylating activating tyrosine residues in Lck and Zap70. We first confirmed the relevance of PTPN22 expression by exploring its expression in multiple human cancer types using The Cancer Genome Atlas (TCGA). PTPN22 expression positively correlated with T cell and M1 macrophage gene signatures and immune regulatory genes, especially inflamed tumor types. Next, we directly investigated the role of PTPN22 in antitumor immunity by comparing in vivo tumor characteristics in wild-type (WT) and PTPN22 knockout (KO) mice. Consistent with our hypothesis, PTPN22 KO mice resisted MC38 and EG7 tumors significantly compared with WT. Mass cytometry (CyTOF) profiling of the immune tumor microenvironment demonstrated that MC38 tumors in PTPN22 KO mice were infiltrated with greater numbers of T cells, particularly CD8+ T cells expressing granzyme B and PD1. To further delineate the effects of PTPN22 KO on TCR signaling, we established an optimized CyTOF panel of 9 phosphorylation sites involved in the TCR signaling pathway, including two enzymatic substrates of PTPN22 (Lck Y394 and Zap70 Y493) and 15 immune subtyping markers. CyTOF phospho-profiling of CD8 T cells from tumor-bearing mouse spleens and the peripheral blood of immunotherapy-naïve cancer patients showed that the phosphorylated state of Zap70 Y493 correlated strongly with granzyme B expression. Furthermore, phospho-profiling of tumor-infiltrating CD8+ T cells (a measure of T cell activation) revealed the highest TCR-pathway phosphorylation levels in memory CD8+ T cells that express PD1. The difference in phosphorylation levels between WT and PTPN22 KO was most pronounced for Lck Y394. Based on these findings, we then hypothesized that PD1 inhibition will further enhance the antitumor immune responses promoted by the lack of PTPN22. Indeed, PTPN22 KO mice bearing MC38 and EG7 tumors responded more significantly to anti-PD1 therapy when compared with tumor-bearing WT mice. Finally, we treated WT tumor bearing mice with two different small molecule inhibitors of PTPN22, one previously published compound, LTV1, and one novel compound, L1 (discovered through structure based synthesis). While both inhibitors phenocopied the PTPN22 KO mice in resisting MC38 tumor growth, L1 treatment gave an immune profile that resembled what was observed in tumor-bearing PTPN22 KO mice. Taken together, our results demonstrate that PTPN22 is a novel systemic target for augmenting antitumor immunity.

  • can they leverage autoimmune data to look at new targets for checkpoint inhibition; we have a long way to go in immunooncology as only less than 30-40% of cancer types respond
  • using Cancer Genome Atlas PTPN22 is associated with autoimmune disorders
  • PTPN22 KO increases many immune cells; macrophages t-cells and when KO in tumors get more t cell infiltrate
  • PTP KO enhances t cell response, and may be driving t cells to exhaustion
  • made a inhibitor or PTPN22; antitumor phenotype when given inhibitor was like KO mice; a PDL1 inhibitor worked in KO mice
  • PTPN22 only in select hematopoetic cells

1:45 PM – 1:50 PM
– Discussion

1:50 PM – 2:00 PM
3399 – Preclinical evaluation of eFT226, a potent and selective eIF4A inhibitor with anti-tumor activity in FGFR1,2 and HER2 driven cancers. Peggy A. Thompson, Nathan P. Young, Adina Gerson-Gurwitz, Boreth Eam, Vikas Goel, Craig R. Stumpf, Joan Chen, Gregory S. Parker, Sarah Fish, Maria Barrera, Eric Sung, Jocelyn Staunton, Gary G. Chiang, Kevin R. Webster. eFFECTOR Therapeutics, San Diego, CA @RuggeroDavide

Abstract: Mutations or amplifications affecting receptor tyrosine kinases (RTKs) activate the RAS/MAPK and PI3K/AKT signaling pathways thereby promoting cancer cell proliferation and survival. Oncoprotein expression is tightly controlled at the level of mRNA translation and is regulated by the eukaryotic translation initiation factor 4F (eIF4F) complex consisting of eIF4A, eIF4E, and eIF4G. eIF4A functions to catalyze the unwinding of secondary structure in the 5’-untranslated region (5’-UTR) of mRNA facilitating ribosome scanning and translation initiation. The activation of oncogenic signaling pathways, including RAS and PI3K, facilitate formation of eIF4F and enhance eIF4A activity promoting the translation of oncogenes with highly structured 5’-UTRs that are required for tumor cell proliferation, survival and metastasis. eFT226 is a selective eIF4A inhibitor that converts eIF4A into a sequence specific translational repressor by increasing the affinity between eIF4A and 5’-UTR polypurine motifs leading to selective downregulation of mRNA translation. The polypurine element is highly enriched in the 5’-UTR of eFT226 target genes, many of which are known oncogenic drivers, including FGFR1,2 and HER2, enabling eFT226 to selectively inhibit dysregulated oncogene expression. Formation of a ternary complex [eIF4A-eFT226-mRNA] blocks ribosome scanning along the 5’-UTR leading to dose dependent inhibition of RTK protein expression. The 5’-UTR sequence dependency of eFT226 translational inhibition was evaluated in cell-based reporter assays demonstrating 10-45-fold greater sensitivity for reporter constructs containing an RTK 5’-UTR compared to a control. In solid tumor cell lines driven by alterations in FGFR1, FGFR2 or HER2, downregulation of RTK expression by eFT226 resulted in decreased MAPK and AKT signaling, potent inhibition of cell proliferation and an induction of apoptosis suggesting that eFT226 could be effective in treating tumor types dependent on these oncogenic drivers. Solid tumor xenograft models harboring FGFR1,2 or HER2 amplifications treated with eFT226 resulted in significant in vivo tumor growth inhibition and regression at well tolerated doses in breast, non-small cell lung and colorectal cancer models. Treatment with eFT226 also decreased RTK protein levels supporting the potential to use these eFT226 target genes as pharmacodynamic markers of target engagement. Further evaluation of predictive markers of sensitivity or resistance showed that RTK tumor models with mTOR mediated activation of eIF4A are most sensitive to eFT226. The association of eFT226 activity in RTK tumor models with mTOR pathway activation provides a means to further enrich for sensitive patient subsets during clinical development. Clinical trials with eFT226 in patients with solid tumor malignancies have initiated.
  • ternary complex formed blocks transcription selectively downregulating RTKs
  • drug binds in 5′ UTR and inhibits translation
  • RTKs activate eIF4 and are also transcribed through them so inhibition destroys this loop;  also with KRAS too
  • main antitumor activity are by an apoptotic mechanisms; refractory tumors are not sensitive to drug induced apoptosis
  • drug inhibits FGFR2 in colorectal cancer
  • drug also effective in HER2+ tumors
  • mTOR mediated eIF4 inhibited by drug
  • they get prolonged antitumor activity after washout of drug because forms this tight terniary complex

2:00 PM – 2:05 PM
– Discussion

2:05 PM – 2:15 PM
3400 – Adenosine receptor antagonists exhibit potent and selective off-target killing of FOXA1-high cancers: Steven M. Corsello, Ryan D. Spangler, Ranad Humeidi, Caitlin N. Harrington, Rohith T. Nagari, Ritu Singh, Vickie Wang, Mustafa Kocak, Jordan Rossen, Amael Madec, Nancy Dumont, Todd R. Golub. Dana-Farber Cancer Institute, Boston, MA, Broad Institute of MIT and Harvard, Cambridge, MA @corsellos

Abstract: Drugs targeting adenosine receptors were originally developed for the treatment of Parkinson’s disease and are now being tested in immuno-oncology clinical trials in combination with checkpoint inhibitors. We recently reported the killing activity of 4,518 drugs against 578 diverse cancer cell lines determined using the PRISM molecular barcoding approach. Surprisingly, three established adenosine receptor antagonists (CGS-15943, MRS-1220, and SCH-58261) showed potent and selective killing of FOXA1-high cancer cell lines without the need for immune cells. FOXA1 is a lineage-restricted transcription factor in luminal breast cancer, hepatocellular carcinoma, and prostate cancer without known small molecule inhibitors. We find that cytotoxic activity is limited to adenosine antagonists with a three-member aromatic core bound to a furan group, thus indicating a potential off-target mechanism of action. To identify genomic modulators of drug response, we performed genome-wide CRISPR/Cas9 knockout modifier screens. Killing by CGS-15943 and MRS-1220 was rescued by knockout of the aryl hydrocarbon receptor (AHR) and its nuclear partner ARNT. In confirmatory studies, knockout of AHR completely rescued killing by CGS-15943 in multiple cell types. Co-treatment with an AHR small molecule antagonist also rescued cell viability. Knockout of adenosine receptors did not alter drug response. Given that AHR is a known transcriptional regulator, we performed global mRNA sequencing to assess transcriptional changes induced by CGS-15943. The top two genes induced were the p450 enzymes CYP1A1 and CYP1B1. To determine sufficiency, we overexpressed CYP1A1 in a resistant cell line. Ectopic CYP1A1 expression sensitized to CGS-15943-mediated killing. Mass spectrometry revealed covalent trapping of a reactive metabolite by glutathione and potassium cyanide following in vitro incubation with liver microsomes. In addition, treatment of breast cancer cells with CGS-15943 for 24 hours resulted in increased γ-H2AX phosphorylation by western blot, indicative of DNA double stranded breaks. In summary, we identified off-target anti-cancer activity of multiple established adenosine receptor antagonists mediated by activation of AHR. Future studies will evaluate the functional contribution of FOXA1 and activity in vivo. Starting from a phenotypic screening hit, we leverage functional genomics to unlock the underlying mechanism of action. This project will pave the way for developing more effective therapies for biomarker-selected cancers, with potential to improve the care of patients with liver, breast, and prostate cancer.

  • developed a chemical library of over 6000 compounds (QC’d) to determine drugs that have antitumor effects
  • used a PRISM barcoded library to make cell lines to screen genotype-phenotype screens
  • for nononcology drugs fourteen drugs had activity in the PRISM assay
  • FOXA1 transcription factor high cancer cells seemed to be inhibited best with adenosine receptor inhibitor found in PRISM assay

2:15 PM – 2:20 PM
– Discussion

2:20 PM – 2:30 PM
3401 – Targeting lysosomal homeostasis in ovarian cancer through drug repurposing: Stefano Marastoni, Aleksandra Pesic, Sree Narayanan Nair, Zhu Juan Li, Ali Madani, Benjamin Haibe-Kains, Bradly G. Wouters, Anthony Joshua. University Health Network, Toronto, ON, Canada, Janssen Inc, Toronto, ON, Canada, The Kinghorn Cancer Centre, Sydney, Australia

Background: Drug repurposing has become increasingly attractive as it avoids the long processes and costs associated with drug discovery. Itraconazole (Itra) is a broad-spectrum anti-fungal agent which has an established broad spectrum of activity in human cell lines including cholesterol antagonism and inhibition of Hedgehog and mTOR pathways. Many in vitro, in vivo and clinical studies have suggested anti-proliferative activity both alone and in combination with other chemotherapeutic agents, in particular in ovarian cancer. This study is aimed at supporting the therapeutic potential of Itra and discovering and repurposing new drugs that can increase Itra anticancer activity as well as identifying new targets in the treatment of ovarian cancer.
Methods: We tested a panel of 32 ovarian cancer cell lines with different doses of Itra and identified a subset of cells which showed significant sensitivity to the drug. To identify genetic vulnerabilities and find new therapeutic targets to combine with Itra, we performed a whole genome sensitivity CRISPR screen in 2 cell lines (TOV1946 and OVCAR5) treated with non-toxic (IC10) concentrations of Itra.
Results: Pathway analysis on the top hits from both the screens showed a significant involvement of lysosomal compartments, and in particular dynamics between trans Golgi network and late endosomes/lysosomes, pathways that are affected by the autophagy inhibitor Chloroquine (CQ). We subsequently demonstrated that the combination of Itra and CQ had a synergistic effect in many ovarian cancer cell lines, even in those resistant to Itra. Further, genetic and pharmacological manipulation of autophagy indicated that upstream inhibition of autophagy is not a key mediator of the Itra/CQ mechanism of action. However, combination of Itra with other lysosomotropic agents (Concanamycin A, Bafilomycin A and Tamoxifen) displayed overlapping activity with Itra/CQ, supporting the lysosomal involvement in sensitizing cells to Itra resulted from the CRISPR screens. Analysis of lysosomal pattern and function showed a combined effect of Itra and CQ in targeting lysosomes and neutralizing their activity.
Conclusion: We identified two FDA approved drugs – CQ and Tamoxifen – that can be used in combination with Itra and exert a potent anti-tumor effect in ovarian cancer by affecting lyosomal function and suggesting a likely dependency of these cells on lysosomal biology. Further studies are in progress.

  • repurposing itraconozole in ovarian cancer potential mechanism of action is pleitropic
  • increasing doses of chloroquine caused OVCA cell death by accumulating in Golgi

2:30 PM – 2:35 PM
– Discussion

2:35 PM – 2:45 PM
3402 – BCAT1 as a druggable target in immuno-oncologyAdonia E. Papathanassiu, Francesca Lodi, Hagar Elkafrawy, Michelangelo Certo, Hong Vu, Jeong Hun Ko, Jacques Behmoaras, Claudio Mauro, Diether Lambrechts. Ergon Pharmaceuticals, Washington, DC, VIB Cancer Centre-KULeuven, Leuven, Belgium, Alexandria University, Alexandria, Egypt, University of Birmingham, Birmingham, United Kingdom, Ergon Pharmaceuticals, Washington, DC, Imperial College London, London, United Kingdom

2:45 PM – 2:50 PM
– Discussion

2:50 PM – 3:00 PM
3403 – Drugging the undruggable: Lessons learned from protein phosphatase 2A: Derek Taylor, Goutham Narla. Case Western Reserve University, Cleveland, OH, University of Michigan, Ann Arbor, MI @gouthamnarla

Abstract: Protein phosphatase 2A (PP2A) is a key tumor suppressor responsible for the dephosphorylation of many oncogenic signaling pathways. The PP2A holoenzyme is comprised of a scaffolding subunit (A), which serves as the structural platform for the catalytic subunit (C) and for an array of regulatory subunits (B) to assemble. Impairment of PP2A is essential for the pathogenesis of many diseases including cancer. In cancer, PP2A is inactivated through a variety of mechanisms including somatic mutation of the Aαsubunit. Our studies show that the most recurrent Aαmutation, P179R, results in an altered protein conformation which prevents the catalytic subunit from binding. Additionally, correcting this mutation, by expressing wild type PP2A Aαin cell lines harboring the P179R mutation, causes a reduction in tumor growth and metastasis. Given its central role in human disease pathogenesis, many strategies have been developed to therapeutically target PP2A.Our lab developed a series of small molecules activators of protein phosphatase 2A. One of our more advanced analogs in this series, DT-061, drives dephosphorylation and degradation of select pathogenic substrates of PP2A such as c-MYC in cellular and in vivo systems. Additionally, we have demonstrated the phosphomimetics of MYC that prevent PP2A mediated dephosphorylation and degradation markedly reduce the anti-tumorigenic activity of this series of PP2A activators further validating the target-substrate specificity of this approach. Specific mutations in the site of drug interaction or overexpression of the DNA tumor virus small T antigen which has been shown to specifically bind to and inactivate PP2A abrogate the in vivo activity of this small molecule series further validating the PP2A specificity of this approach. Importantly, treatment with DT-061 results in tumor growth inhibition in an array of in vivocancer models and marked regressions in combination with MEKi and PARPi.To further define the mechanism of action of this small molecule series, we have used cryo-electron microscopy (cryo-EM) to visualize directly theinteraction between DT-061 and a PP2A heterotrimeric complex. We have identified molecular interactions between DT-061 and all three PP2A subunits that prevent dissociation of the active enzyme through the marked prolongation of the kOFF of the native complex. Furthermore, we demonstrate that DT-061 specifically stabilizes the B56α-PP2A holoenzyme in a fully assembled, active state to dephosphorylate oncogenic targets such as c-MYC in both cellular and in vivo systems. This 3.6 Å structure identifies dynamic molecular interactions between the three distinct PP2A subunits and highlight the inherent mechanisms of PP2A complex assembly and disassembly in both cell free and cellular systems. Thus, our findings provide fundamental insights into PP2A complex assembly and regulation, identify a unique interfacial stabilizing mode of action for the therapeutic targeting of previously undruggable proteins, and aid in the development of phosphatase-based therapeutics tailored against disease specific phosphor-protein targets. The marriage of multidisciplinary scientific practices has allowed us to present here a previously unrecognized therapeutic strategy of complex stabilization for the activation of endogenous disease combating enzymes.

  • Reactivating PP2A; dephosphorylation of proteins (serine/threonine phosphatases); regulates multiple processes in the cell
  • SV40T has an antigen that inactivates PP2A; recurrent mutations in high grade endometrial cancers
  • P179R mutation promotes uterine tumor formation (also in a distal tubule ligation model)
  • project started in a phenotypic screen that tricyclic antidepressants could have an off target which was phosphatase activators (uncoupling GPCR from anticancer activity)
  • small T antigen block the activity of these small molecule activators;
  • acts as a molecular glue to bring the activators with a heterotrimer of phosphatases
  • so their small molecule activators effective in triple negative breast cancers;  one of targets of PP2A is MYC
  • question: have not yet seen resistance to these compounds but are currently looking at this

 

3:00 PM – 3:05 PM
– Discussion

3:05 PM – 3:15 PM
3404 – Inhibition of BCL10-MALT1 interaction to treat diffuse large B-cell lymphomaH: eejae Kang, Dong Hu, Marcelo Murai, Ahmed Mady, Bill Chen, Zaneta Nikolovska-Coleska, Linda M. McAllister-Lucas, Peter C. Lucas. University of Pittsburgh School of Medicine, Pittsburgh, PA, Merck, Kenilworth, NJ, University of Michigan School of Medicine, Ann Arbor, MI, University of Pittsburgh School of Medicine, Pittsburgh, PA, University of Michigan School of Medicine, Ann Arbor, MI, UPMC Children’s Hospital, Pittsburgh, PA

Abstract: The CARMA1/BCL10/MALT1 (CBM) signaling complex mediates antigen receptor-induced activation of NF-kB in lymphocytes to support normal adaptive immunity. As the effector protein of the complex, MALT1 exhibits two activities: protease and scaffolding activities. Gain-of-function mutations in the CARMA1 moiety or its upstream regulators trigger antigen-independent assembly of oligomeric CBM complexes, leading to constitutive activation of MALT1, unregulated NF-kB activity, and development of Activated B-Cell subtype of Diffuse Large B-Cell Lymphoma (ABC-DLBCL). Existing MALT1 inhibitors block only MALT1 protease activity, causing incomplete and unbalanced inhibition of MALT1, and have the potential for inducing autoimmune side effects. Since MALT1 is recruited to the CBM complex via its interaction with BCL10, we sought to identify inhibitors of BCL10-MALT1 interaction in order to target both the protease and scaffolding activities of MALT1 to treat ABC-DLBCL.
Our previous work suggested that an antibody-epitope-like interface governs the interaction between BCL10 and MALT1, so that a therapeutic opportunity exists for developing a small molecule inhibitor of the interaction to terminate inappropriate CBM activity. Using co-immunoprecipitation studies, a mammalian two-hybrid system, and surface plasmon resonance (SPR), we confirmed that BCL10 residues 107-119 and the tandem Ig-like domains of MALT1 are critical for this interaction. We then performed a structure-guided in silico screen of 3 million compounds, based on a computational model of the BCL10-MALT1 interaction interface, to identify compounds with potential for disrupting the interaction.
Compound 1 from the initial screening hits showed dose-responsive inhibition of BCL10-MALT1 interaction in both SPR and ELISA-based assays. Functionally, Compound 1 inhibits both MALT1 protease and scaffolding activities in Jurkat T cells, as demonstrated by its inhibition of CD3/CD28-induced RelB and N4BP1 cleavage, and inhibition of IKK phosphorylation, respectively. Compound 1 also blocks IL-2 transcription and IL-2 secretion by PMA/ionomycin-treated Jurkat T cells, as well as constitutive CBM-dependent secretion of IL-6 and IL-10 by ABC-DLBCL cells. Accordingly, Compound 1 selectively suppresses the growth of ABC-DLBCL cell lines, but does not affect the growth of MALT1-independent GCB-DLBCL cell lines.
In conclusion, we have identified an early-stage small molecule compound that inhibits the BCL10-MALT1 interaction, MALT1 protease and scaffolding activities, downstream CBM-dependent signaling, and ABC-DLBCL cell growth. Structure-guided modification of this lead compound is underway to further develop a new class of protein-protein interaction inhibitors that could provide more efficacious blockade of MALT1, while offering protection from undesirable autoimmune side effects in the treatment of this aggressive form of lymphoma.

3:15 PM – 3:20 PM
– Discussion

3:20 PM – 3:30 PM
– Closing RemarksJohn S. Lazo. University of Virginia, Charlottesville, VA

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from The American Association for Cancer Research aacr.org:

 

AACR Congratulates Dr. William G. Kaelin Jr., Sir Peter J. Ratcliffe, and Dr. Gregg L. Semenza on 2019 Nobel Prize in Physiology or Medicine

10/7/2019

PHILADELPHIA — The American Association for Cancer Research (AACR) congratulates Fellow of the AACR Academy William G. Kaelin Jr., MDSir Peter J. Ratcliffe, MD, FRS, and AACR member Gregg L. Semenza, MD, PhD, on receiving the 2019 Nobel Prize in Physiology or Medicine for their discoveries of how cells sense and adapt to oxygen availability.

Kaelin, professor of medicine at the Dana-Farber Cancer Institute and Harvard Medical School in Boston; Ratcliffe, director of Clinical Research at the Francis Crick Institute in London; and Semenza, director of the Vascular Program at the Institute for Cell Engineering at Johns Hopkins University School of Medicine in Baltimore, are being recognized by the Nobel Assembly at the Karolinska Institute for identifying the molecular machinery that regulates the activity of genes in response to varying levels of oxygen, which is one of life’s most essential adaptive processes. Their work has provided basic understanding of several diseases, including many types of cancer, and has laid the foundation for the development of promising new approaches to treating cancer and other diseases.

Kaelin, Ratcliffe, and Semenza were previously recognized for this work with the 2016 Lasker-DeBakey Clinical Medical Research Award.

Kaelin’s research focuses on understanding how mutations affecting tumor-suppressor genes cause cancer. As part of this work, he discovered that a tumor-suppressor gene called von Hippel–Lindau (VHL) is involved in controlling the cellular response to low levels of oxygen. Kaelin’s studies showed that the VHL protein binds to hypoxia-inducible factor (HIF) when oxygen is present and targets it for destruction. When the VHL protein is mutated, it is unable to bind to HIF, resulting in inappropriate HIF accumulation and the transcription of genes that promote blood vessel formation, such as vascular endothelial growth factor (VEGF). VEGF is directly linked to the development of renal cell carcinoma and therapeutics that target VEGF are used in the clinic to treat this and several other types of cancer.

Kaelin has been previously recognized with numerous other awards and honors, including the 2006 AACR-Richard and Hinda Rosenthal Award.

Ratcliffe independently discovered that the VHL protein binds to HIF. Since then, his research has focused on the molecular interactions underpinning the binding of VHL to HIF and the molecular events that occur in low levels of oxygen, a condition known as hypoxia. Prior to his work on VHL, Ratcliffe’s research contributed to elucidating the mechanisms by which hypoxia increases levels of the hormone erythropoietin (EPO), which leads to increased production of red blood cells.

Semenza’s research, which was independent of Ratcliffe’s, identified in exquisite detail the molecular events by which the EPO gene is regulated by varying levels of oxygen. He discovered HIF and identified this protein complex as the oxygen-dependent regulator of the EPO gene. Semenza followed up this work by identifying additional genes activated by HIF, including showing that the protein complex activates the VEGF gene that is pivotal to the development of renal cell carcinoma.

The recognition of Kaelin and Semenza increases the number of AACR members to have been awarded a Nobel Prize to 70, 44 of whom are still living.

The Nobel Prize in Physiology or Medicine is awarded by the Nobel Assembly at the Karolinska Institute for discoveries of major importance in life science or medicine that have changed the scientific paradigm and are of great benefit for mankind. Each laureate receives a gold medal, a diploma, and a sum of money that is decided by the Nobel Foundation.

The Nobel Prize Award Ceremony will be Dec. 10, 2019, in Stockholm.

Please find following articles on the Nobel Prize and Hypoxia in Cancer on this Open Access Journal:

2018 Nobel Prize in Physiology or Medicine for contributions to Cancer Immunotherapy to James P. Allison, Ph.D., of the University of Texas, M.D. Anderson Cancer Center, Houston, Texas. Dr. Allison shares the prize with Tasuku Honjo, M.D., Ph.D., of Kyoto University Institute, Japan

The History, Uses, and Future of the Nobel Prize, 1:00pm – 6:00pm, Thursday, October 4, 2018, Harvard Medical School

2017 Nobel prize in chemistry given to Jacques Dubochet, Joachim Frank, and Richard Henderson  for developing cryo-electron microscopy

Tumor Ammonia Recycling: How Cancer Cells Use Glutamate Dehydrogenase to Recycle Tumor Microenvironment Waste Products for Biosynthesis

Hypoxia Inducible Factor 1 (HIF-1)[7.9]

 

 

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Brain surgeons’ research prompts new approach to cancer treatment

 

Reporter: Alex Crystal

 

UPDATED on 5/22/2019

For treating high-grade gliomas, an aggressive brain cancer, the combination therapy of experimental agents Toca 511 [immunotherapy] and Toca FC [chemotherapy] failed against chemotherapy or Avastin to show extended survival

  • Tocagen said Tuesday its brain cancer trial has not been able to show so far that a combination therapy of experimental agents Toca 511 and Toca FC extended survival when compared with chemotherapy or Avastin. The announcement was based on an interim analysis and the study will proceed to a final readout later this year.
  • Investors took the announcement as a sign that the trial is likely to fail, as shares fell 35% Wednesday to a record low. SVB Leerink analyst Daina Graybosch raised questions about the biological effect of the combination therapy as well as earlier-stage trial designs that Tocagen used to justify moving swiftly into a pivotal trial.
  • Toca 511, an immunotherapy, and Toca FC, a chemotherapy, aim to treat high-grade gliomas, an aggressive brain cancer. In the recurrent patients Tocagen hopes to treat, average survival is no more than about a year.

SOURCE

https://www.biopharmadive.com/news/tocagen-brain-cancer-trial-continues-stock-drop/555360/

 

Brain surgeons turn to basic science to fight childhood brain cancer @Stanford Medical School

By Krista Conger

 

Residents Teresa and Jamie Purzner stepped away from Neurosurgery to focus on research of medulloblastoma. The pair spent six years researching the cause of brain tumors before publishing their findings. They discovered a phosphate-adding protein called CK2 linked to the growth of this type of cancer. Afterword, they applied this finding by putting a CK2 inhibitor in mice implanted with medulloblastoma cells. After successful trials on animals, the duo combined efforts with the Stanford SPARK program to begin the development of drugs. Their efforts were rewarded and the pair went ahead with phase 1-2 clinical trials of the only known CK2 inhibitor, CX-4945. It is yet to be seen how successful their efforts will be in treating children with hedgehog-dependent medulloblastoma, but this approach opens up an entirely new and promising field of research.

SOURCE

http://med.stanford.edu/news/all-news/2019/05/brain-surgeons-turn-to-basic-science-to-fight-childhood-brain-cancer.html

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Lesson 10 on Cancer, Oncogenes, and Aberrant Cell Signal Termination in Disease for #TUBiol3373

Curator: Stephen J. Williams

Please click on the following file to get the Powerpoint Presentation for this lecture

cell signaling 10 lesson_SJW 2019

There is a good reference to read on The Hallmarks of Cancer published first in 2000 and then updated with 2 new hallmarks in 2011 (namely the ability of cancer cells to reprogram their metabolism and 2. the ability of cancer cells to evade the immune system)

a link to the PDF is given here:

hallmarks2000

hallmarks2011

Please also go to other articles on this site which are relevant to this lecture.  You can use the search box in the upper right hand corner of the Home Page or these are few links you might find interesting

Development of Chemoresistance to Targeted Therapies: Alterations of Cell Signaling & the Kinome

Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation: a Compilation of Articles in the Journal http://pharmaceuticalintelligence.com

Feeling the Heat – the Link between Inflammation and Cancer

Lesson 4 Cell Signaling And Motility: G Proteins, Signal Transduction: Curations and Articles of reference as supplemental information: #TUBiol3373

Immunotherapy Resistance Rears Its Ugly Head: PD-1 Resistant Metastatic Melanoma and More

Novel Mechanisms of Resistance to Novel Agents

 

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Gender affects the prevalence of the cancer type, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Gender of a person can affect the kinds of cancer-causing mutations they develop, according to a genomic analysis spanning nearly 2,000 tumours and 28 types of cancer. The results show striking differences in the cancer-causing mutations found in people who are biologically male versus those who are biologically female — not only in the number of mutations lurking in their tumours, but also in the kinds of mutations found there.

 

Liver tumours from women were more likely to carry mutations caused by a faulty system of DNA mending called mismatch repair, for instance. And men with any type of cancer were more likely to exhibit DNA changes thought to be linked to a process that the body uses to repair DNA with two broken strands. These biases could point researchers to key biological differences in how tumours develop and evolve across sexes.

 

The data add to a growing realization that sex is important in cancer, and not only because of lifestyle differences. Lung and liver cancer, for example, are more common in men than in women — even after researchers control for disparities in smoking or alcohol consumption. The source of that bias, however, has remained unclear.

In 2014, the US National Institutes of Health began encouraging researchers to consider sex differences in preclinical research by, for example, including female animals and cell lines from women in their studies. And some studies have since found sex-linked biases in the frequency of mutations in protein-coding genes in certain cancer types, including some brain cancers and advanced melanoma.

 

But the present study is the most comprehensive study of sex differences in tumour genomes so far. It looks at mutations not only in genes that code for proteins, but also in the vast expanses of DNA that have other functions, such as controlling when genes are turned on or off. The study also compares male and female genomes across many different cancers, which can allow researchers to pick up on additional patterns of DNA mutations, in part by increasing the sample sizes.

 

Researchers analysed full genome sequences gathered by the International Cancer Genome Consortium. They looked at differences in the frequency of 174 mutations known to drive cancer, and found that some of these mutations occurred more frequently in men than in women, and vice versa. When they looked more broadly at the loss or duplication of DNA segments in the genome, they found 4,285 sex-biased genes spread across 15 chromosomes.

 

There were also differences found when some mutations seemed to arise during tumour development, suggesting that some cancers follow different evolutionary paths in men and women. Researchers also looked at particular patterns of DNA changes. Such patterns can, in some cases, reflect the source of the mutation. Tobacco smoke, for example, leaves behind a particular signature in the DNA.

 

Taken together, the results highlight the importance of accounting for sex, not only in clinical trials but also in preclinical studies. This could eventually allow researchers to pin down the sources of many of the differences found in this study. Liver cancer is roughly three times as common in men as in women in some populations, and its incidence is increasing in some countries. A better understanding of its aetiology may turn out to be really important for prevention strategies and treatments.

 

References:

 

https://www.nature.com/articles/d41586-019-00562-7?utm_source=Nature+Briefing

 

https://www.nature.com/news/policy-nih-to-balance-sex-in-cell-and-animal-studies-1.15195

 

https://www.ncbi.nlm.nih.gov/pubmed/26296643

 

https://www.biorxiv.org/content/10.1101/507939v1

 

https://www.ncbi.nlm.nih.gov/pubmed/25985759

 

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