Author: Kathryn Atkins

Novel Antibody Drug Conjugate Improves Murine Acute Myeloid Leukemia

Researchers from Astellas Pharma Inc. investigated the efficacy of a novel antibody drug conjugate combined with venetoclax and azacitidine in a mouse model of acute myeloid leukemia.

Novel Antibody Drug Conjugate Improves Murine Acute Myeloid Leukemia

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The average age of patients with acute myeloid leukemia (AML) is 67 years old. Older adults generally have a lower tolerance for treatments that exhibit high off-target toxicity. Additionally, chemotherapy-relapsed or -refractory (R/R) AML patients are often at an advanced stage of disease and are therefore more likely to have comorbidities that may reduce their tolerance for harsh treatments.

Thus, pharmaceutical AML drugs with high efficacy and low toxicity are in high demand. Antibody drug conjugates (ADCs) are emerging as promising therapeutic approaches to more safely treat hematological malignancies by reducing side effects. ADCs are designed to decrease damage to healthy tissues by specifically targeting tumor-associated antigens attached to cancer cells.

“Antibody drug conjugates (ADC) are one of the modalities that aims to dissociate drug efficacy from toxicity. ADC consists of three components: antibody specific for tumor associated antigen, drug linker and cytotoxic payload.”

Astellas Pharma

Recently, researchers from Astellas Pharma Inc. (a pharmaceutical company in Japan) developed ASP1235—a novel ADC that targets Fms-like tyrosine kinase 3 (FLT3). In more than 90% of AML patients, FLT3 is overexpressed on leukemic blasts. ASP1235 is designed to target FLT3-positive leukemia cells and deliver the cytotoxic drug payload to these cells. However, this drug alone was found to have only a mild effect on AML cells, prompting researchers to assess the efficacy of ASP1235 in combination with other drugs.

In a new study, Astellas Pharma researchers Hirofumi Tsuzuki, Tatsuya Kawase, Taisuke Nakazawa, Masamichi Mori, and Taku Yoshida investigated the efficacy of ASP1235 combined with venetoclax (an anti-apoptotic agent) and azacitidine (a DNA methyltransferase inhibitor) in an experimental mouse model of AML. Their research paper was published in Oncotarget on December 20, 2022, and entitled, “Anti-tumor effect of antibody drug conjugate ASP1235 targeting Fms-like tyrosine kinase 3 with venetoclax plus azacitidine in an acute myeloid leukemia xenograft mouse model.”

“In this study, we sought to evaluate the therapeutic effect of ASP1235 in combination with venetoclax plus azacitidine, a novel standard-of-care treatment for elderly AML patients, in ASP1235 poor sensitive AML cells.”

The Study

The researchers first aimed to determine an AML cell line that was only partially sensitive to ASP1235 monotherapy. They determined the THP-1 cell line was appropriate for further investigation. They compared FLT3 and Bcl-2 expression levels in THP-1 cells with primary leukemic cells from chemotherapy R/R AML patients to consider the clinical relevance of each. In THP-1 cells, the expression levels of FLT3 and Bcl-2 were found to be clinically relevant.

“It has been reported that the proportion of patients showing high Bcl-2 expression was greater in chemotherapy R/R AML patients compared to that in newly diagnosed patients [4]. Thus, we investigated the expression levels of Bcl-2 together with FLT3 to further consider the relevance of THP-1 cells for evaluation on the combination treatment with venetoclax.”

To confirm their in vitro findings, they used a THP-1 xenograft mouse model for in vivo investigation of ASP1235 sensitivity. Their findings indicated that the THP-1 cell was a partially sensitive preclinical model to ASP1235. Next, the researchers evaluated the in vivo efficacy of ASP1235 in combination with venetoclax plus azacitidine using the THP-1 xenograft mouse model. The results showed that the combination therapy induced a significant reduction in tumor size compared to ASP1235 monotherapy and the other two drugs alone. This suggests that ASP1235 has an enhanced anti-tumor effect in combination with venetoclax and azacitidine.

“Consistent with in vitro observations in Figure 4, triple combination treatment with ASP1235, venetoclax and azacitidine induced tumor regression, and the anti-tumor effect of the triple combination was much stronger than that of ASP1235 single agent or venetoclax plus azacitidine without obvious body weight loss (Figure 5).”

Figure 5: ASP1235 showed enhanced anti-tumor effect in combination with venetoclax and azacitidine in THP-1 xenograft mouse model.
Figure 5: ASP1235 showed enhanced anti-tumor effect in combination with venetoclax and azacitidine in THP-1 xenograft mouse model.

Conclusions

The findings of this study suggest that the combination therapy of ASP1235, venetoclax and azacitidine can be an effective treatment option for elderly patients or patients with chemotherapy R/R AML. This combination therapy induced a significant reduction in xenograft tumors in the THP-1 mouse model, suggesting that it may be a promising therapeutic approach for AML patients. Further clinical trials are needed to confirm these results.

“In conclusion, the triple combination treatment of ASP1235, venetoclax and azacitidine has the potential to benefit AML patients, and there is a possibility to expect the combination effect of ASP1235 and venetoclax regimen in FLT3 positive cancers beyond AML.”

Click here to read the full research paper published by Oncotarget

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Oncotarget is an open-access journal that publishes primarily oncology-focused research papers in a continuous publishing format. These papers are available at no cost to readers on Oncotarget.com. Open-access journals have the power to benefit humanity from the inside out by rapidly disseminating information that may be freely shared with researchers, colleagues, family, and friends around the world.

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A New Method of Targeting Exosomes in Precision Medicine

Oncotarget published a new editorial perspective by Dr. Mujib Ullah, entitled, “The future of bioorthogonal-chemistry for targeting of exosomes in precision medicine.”

A New Method of Targeting Exosomes in Precision Medicine
Figure 1: Schematic illustration showing tracking of exosomes labeled by phospholipid-based bioorthogonal conjugation.
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Extracellular vesicles are membrane-bound vehicles released by cells into the extracellular environment. There are three known types of extracellular vesicles: microvesicles, apoptotic bodies and exosomes. Discovered in 1983, exosomes can be defined as packets of bio-nanoparticles released by cells containing bioactive molecules such as proteins, lipids and nucleic acids. Exosomes can deliver their payload to other cells and are now also recognized for their role in cell-to-cell communication. This makes exosomes attractive targets for precision medicine tactics. However, targeting exosomes is challenging due to their nano-size and reactive contents. Bioorthogonal-chemistry may provide a new approach for targeting exosomes in precision medicine.

“Bioorthogonal is the name of a chemical reaction that can occur inside of living cells without interfering the naïve biological process [1, 2].”

Bioorthogonal-chemistry allows for the attachment of bioactive molecules to the surface of exosomes without disturbing the native environment. Developed in the early 2000s, this strategy could potentially be used to deliver therapeutic drugs or bioactive molecules directly to the target site with high precision. Bioorthogonal-chemistry is still at an early stage of development, but it holds promise in precision medicine for the treatment of cancer and other illnesses. By providing a way to target exosomes with bioactive molecules, bioorthogonal-chemistry could help to significantly improve the efficacy of medical treatments. It could also reduce the side effects of current treatments and increase safety for patients.

“The concept of bioorthogonal chemistry has inspired a generation of biologists to think about RNA editing and bioengineering of exosomes [3, 4].”

On December 6, 2022, Oncotarget published a new editorial perspective by Dr. Mujib Ullah from Stanford University, entitled, “The future of bioorthogonal-chemistry for targeting of exosomes in precision medicine.”

In this short editorial perspective, Dr. Ullah discussed current exosome-loading techniques, including electroporation, heat shock, sonication, and ultracentrifugation. He wrote that these techniques are disruptive and potentially ineffective methods of exosome loading. On the other hand, he explained that using a precise, targeted bioorthogonal reaction can overcome the aforementioned issues. Dr. Ullah listed nine questions at the end of his editorial perspective. He believes these important questions must be answered in order to showcase the potential of bioorthogonal reactions in future clinical biomedical applications:

  1. Can bioorthogonal chemistry help in the development of more powerful bioimaging and biosensing techniques?
  2. Can the combination of exosomes with biorthogonal chemistry overcome some of the current translational hurdles in precision medicine?
  3. Can new drugs be designed inside humans?
  4. Can the exosomes cargo be detected by conjugation chemistry?
  5. Can we track the metabolites encapsulated inside the exosomes?
  6. Can pharmaceuticals be synthesized inside living system?
  7. How many orthogonal reactions can be performed in one time?
  8. What is the half life of these reactions?
  9. Biorthogonal reactions are rapid but what is the speed of reactions? 

Click here to read the full editorial perspective published by Oncotarget

ONCOTARGET VIDEOS: YouTube | LabTube | Oncotarget.com

Oncotarget is an open-access journal that publishes primarily oncology-focused research papers in a continuous publishing format. These papers are available at no cost to readers on Oncotarget.com. Open-access journals have the power to benefit humanity from the inside out by rapidly disseminating information that may be freely shared with researchers, colleagues, family, and friends around the world.

For media inquiries, please contact media@impactjournals.com.

Plasma Growth Hormone in HCC: A Biomarker of Response to Atezo/Bev?

In a new study, researchers investigated the plasma growth hormone as a potential biomarker of response to atezolizumab and bevacizumab in advanced hepatocellular carcinoma patients.

Plasma Growth Hormone in HCC: A Biomarker of Response to Atezo/Bev?

The Trending With Impact series highlights Oncotarget publications attracting higher visibility among readers around the world online, in the news, and on social media—beyond normal readership levels. Look for future science news about the latest trending publications here, and at Oncotarget.com.

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Hepatocellular carcinoma (HCC) is a highly aggressive cancer of the liver with a very poor prognosis; many patients pass away within a year of diagnosis. Currently, there is no effective screening method for HCC and thus, 80% of patients are diagnosed at advanced stages. This makes treatment difficult and often unsuccessful. As a result, new treatments for HCC are constantly being explored.

Atezolizumab and bevacizumab are two standard therapies used to treat unresectable, advanced HCC. However, researchers Yehia I. Mohamed, Dan G. Duda, Muhammad O. Awiwi, Sunyoung S. Lee, Lina Altameemi, Lianchun Xiao, Jeffrey S. Morris, Robert A. Wolff, Khaled M. Elsayes, Rikita I. Hatia, Aliya Qayyum, Shadi M. Chamseddine, Asif Rashid, James C. Yao, Armeen Mahvash, Manal M. Hassan, Hesham M. Amin, and Ahmed Omar Kaseb from MD Anderson Cancer Center, Massachusetts General Hospital, Harvard Medical School, Michigan State University, and University of Pennsylvania Perelman School of Medicine noticed a significant gap in research on biomarkers of response in advanced HCC patients treated with atezolizumab plus bevacizumab. The team conducted a new study aimed at beginning to close this gap. On December 6, 2022, their research paper was published in Oncotarget’s Volume 13, entitled, “Plasma growth hormone is a potential biomarker of response to atezolizumab and bevacizumab in advanced hepatocellular carcinoma patients.”

“This study investigated the biomarker value of plasma growth hormone (GH) level as a potential biomarker to predict outcome in unresectable HCC patients treated with current standard therapy, atezolizumab plus bevacizumab (Atezo/Bev).”

The Study

Plasma growth hormone (GH) is a potential biomarker that had not previously been evaluated in relation to this treatment regimen in HCC before. In this study, the researchers included 37 patients with advanced HCC. The patients received atezolizumab plus bevacizumab at the MD Anderson Cancer Center between June 2018 and November 2021. The median age of the patients was 67 years old, and the vast majority were male (83.8%). 

The team measured plasma GH levels, progression-free survival (PFS) and overall survival (OS). Plasma GH levels were measured by ELISA and used to stratify the HCC patients into GH-high and GH-low groups. The Kaplan-Meier method was used to calculate median OS and PFS. The Log-rank test was used to compare survival outcomes between GH-high and -low groups.

“To the best of our knowledge, this is the first study to assess clinical prognostic value of plasma GH level in patients who have received atezolizumab plus bevacizumab in clinical setting.”

The results of the study showed that plasma GH levels significantly correlated with OS. At the time of the analysis, the one-year survival rate was 70% among GH-low patients and 33% among GH-high patients. OS was significantly superior in GH-low compared to GH-high patients. PFS showed a non-significant trend in favor of GH-low patients compared to the GH-high group.

Conclusion

“Despite the small data size, plasma GH levels were strongly predictive of the disease outcome in patients treated with Atezo/Bev.”

The study concluded that plasma GH levels may be a promising biomarker for predicting response to atezolizumab plus bevacizumab in advanced HCC patients. Further, plasma GH levels may be used to stratify advanced HCC patients into high- and low-risk groups. The researchers recommend further research in larger scale and different populations to validate the findings and explore plasma GH levels as a potential biomarker of response to this treatment regimen in HCC.

“In conclusion, our study demonstrate[s] that plasma GH represents a candidate biomarker for predicting treatment outcomes in patients with advanced HCC treated with Atezo/Bev. Future studies in larger randomized clinical trial and with a more diverse ethnic, race, and gender background are warranted to further validate these findings.”

Click here to read the full research paper published by Oncotarget

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Oncotarget is an open-access journal that publishes primarily oncology-focused research papers in a continuous publishing format. These papers are available at no cost to readers on Oncotarget.com. Open-access journals have the power to benefit humanity from the inside out by rapidly disseminating information that may be freely shared with researchers, colleagues, family, and friends around the world.

For media inquiries, please contact media@impactjournals.com.

Biomarkers May Predict Neoadjuvant Chemosensitivity in Bladder Cancer

In a new study, researchers aimed to identify and validate predictive biomarkers of response to neoadjuvant chemotherapy (NAC) in patients with muscle-invasive bladder cancer (MIBC).

Biomarkers May Predict Neoadjuvant Chemosensitivity in Bladder Cancer
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Neoadjuvant chemotherapy (NAC) is a type of cancer treatment involving the administration of chemotherapy drugs before surgery. The goal of NAC is to shrink the tumor(s) in order to make it/them easier to remove during surgery and to decrease the chance of cancer recurrence after treatment. NAC is typically well tolerated by patients and has been shown to improve outcomes in patients with bladder cancer.

Predictive biomarkers are being increasingly used in oncology to identify patients who are likely to respond to chemotherapy. In the past, the decision to administer chemotherapy was based on tumor type and stage. However, it is now understood that there is considerable heterogeneity within these groups, and that not all patients will respond to the same treatment. Predictive biomarkers can help to overcome this challenge by identifying those patients who are most likely to benefit from chemotherapy.

There are a number of different types of predictive biomarkers, which can be divided into two broad categories: tumor biomarkers and host biomarkers. Tumor biomarkers are usually specific to the tumor type and can include markers of cell proliferation and DNA repair. Host biomarkers are usually found in the blood or other bodily fluids and can include markers of inflammation, immune function and metabolism. The use of predictive biomarkers has the potential to improve the efficacy of chemotherapy and reduce toxicity by avoiding its use in patients who are unlikely to benefit.

The Study

In a new study, researchers Neal Murphy, Andrew J. Shih, Paras Shah, Oksana Yaskiv, Houman Khalili, Anthony Liew, Annette T. Lee, and Xin-Hua Zhu from Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Northwell Health Cancer Institute, Feinstein Institutes for Medical Research, and Mayo Clinic aimed to develop and validate a predictive biomarker panel for response to NAC in patients with muscle-invasive bladder cancer (MIBC). Their research paper was published on November 2, 2022, in Oncotarget’s Volume 13, entitled, “Predictive molecular biomarkers for determining neoadjuvant chemosensitivity in muscle invasive bladder cancer.”

“The NAC non-responders suffer from unnecessary adverse effects and a delay in time to cystectomy leading to worse overall survival [9, 10]. Subsequently, there remains a critical need to understand the molecular biology behind NAC responsiveness, in order to better tailor individual NAC therapy.”

The purpose of this research was to “develop a molecular signature that can identify MIBC NAC responders (R) and non-responders (NR) using a cohort of known NAC response phenotypes, and better understand differences in molecular pathways and subtype classifications between NAC R and NR.” Researchers identified a total of 26 patients with known NAC response for inclusion in this study. These patients were assigned at random to either the discovery or validation cohort. The discovery cohort consisted of seven NAC responders and 11 non-responders. The validation cohort consisted of three responders and five non-responders.

Transurethral resection of bladder tumor (TURBT) specimens from the Northwell Health pathology department were received as formalin-fixed, paraffin-embedded (FFPE) tissue blocks. Pathologic response was determined at the time of cystectomy. Messenger RNA (mRNA) and microRNA (miRNA) from the FFPE blocks were sequenced using RNAseq and qPCR, respectively.

“To our knowledge, our study is the first to use combined differential mRNA and miRNA expression in MIBC to identify a NAC response signature.”

The Results

“We report significant gene sets associated with NAC response phenotype, as well as three multigene and miRNA signatures generated by CCA that can be used to potentially classify NAC response.”

In the discovery cohort, the researchers found that 2309 genes were differentially expressed between the NAC responders and non-responders. In the validation cohort, 602 genes and 13 miRNA were differentially expressed. Canonical correlation (CC) analysis found that three CCs (CC13: nucleoside triphosphate metabolic process; CC16: cell cycle and cellular response to DNA damage; and CC17: DNA packaging complex) were differentiated in the discovery and validation datasets. As far as MIBC subtypes, the MD Anderson p53-like subtype, CIT MC4 subtype and Consensus Class stroma-rich subtype had the strongest correlation with a non-responder phenotype. There were no subtypes that had strong correlations with the responder phenotype.

“In conclusion, our results identify molecular signatures that can be used to differentiate MIBC NAC responders versus non-responders. We have presented the salient molecular pathways and relevant genes, including mitochondrial response gene expression (MRPS12, MRPS34, MRPS28, MRPS14, and MRPS2), DNA replication initiation, and DNA unwinding and DNA damage (MCM2-3, MCM5-6 and XAP , ELK4, and FOXA3) that can be further analyzed to better understand NAC response. The above mentioned genes derived from their respective three pathways may be selected as part of a NAC response biomarker panel. In addition, we have highlighted the utility of molecular subtyping in relation to NAC response. If validated in a larger cohort, these findings may help deliver chemotherapy to those patients most likely to respond.”

Conclusion

Neoadjuvant chemotherapy is a promising treatment option for muscle-invasive bladder cancer patients, however, there is a class of patients who do not respond to chemotherapy. The results of this study implicate several different types of biomarkers that may be associated with chemosensitivity in MIBC patients. Further research is needed to validate these findings. Ultimately, if validated, these biomarkers could help to spare non-responders from side effects associated with ineffective and unnecessary chemotherapy.

“Our results identify molecular signatures that can be used to differentiate MIBC NAC R versus NR, salient molecular pathway differences, and highlight the utility of molecular subtyping in relation to NAC response.”

Click here to read the full research paper published by Oncotarget

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Oncotarget is an open-access journal that publishes primarily oncology-focused research papers in a continuous publishing format. These papers are available at no cost to readers on Oncotarget.com. Open-access journals have the power to benefit humanity from the inside out by rapidly disseminating information that may be freely shared with researchers, colleagues, family, and friends around the world.

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New Target Fights Ferroptosis- and Radio-Resistance in Lung Cancers

Researchers published a research perspective about a recent study that uncovered FSP1 as a novel target gene that mediates ferroptosis resistance and radioresistance in lung cancer cells.

Figure 1: KEAP1-NRF2 axis and its molecular effectors in the regulation of ferroptosis.
Figure 1: KEAP1-NRF2 axis and its molecular effectors in the regulation of ferroptosis.
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Ferroptosis is a type of cell death caused by the accumulation of iron and lipid peroxides in cells. Cancer cells are often resistant to ferroptosis, which allows them to survive and proliferate. Radioresistance is another common feature of cancer cells that allows them to resist the effects of radiation therapy.

A new research paper (published on April 22, 2022) identified ferroptosis suppressor protein 1 (FSP1) as a novel KEAP1/NRF2 target gene and demonstrated that FSP1 plays an essential role in NRF2-mediated ferroptosis resistance and radioresistance in KEAP1-deficient lung cancer cells. 

Recently, researchers Nsengiyumva Emmanuel, Hongen Li, Jing Chen, and Yilei Zhang from Xi’an Jiaotong University, Ruyang People’s Hospital and Shaanxi Jiuzhou Biomedical Science and Technology Group wrote a paper about the implications of these findings. On October 19, 2022, their research perspective was published in Oncotarget’s Volume 13, entitled, “FSP1, a novel KEAP1/NRF2 target gene regulating ferroptosis and radioresistance in lung cancers.”

“In a recent study by Pranavi Koppula et al. from The University of Texas MD Anderson Cancer Center, FSP1 was demonstrated as a novel target of NRF2 and to play a vital role in KEAP1/NRF2-mediated ferroptosis regulation [13], which reveals the important role of genetic regulation of FSP1 in cancer development.”

The KEAP1-NRF2 regulatory pathway is crucial for protecting cells against oxidative damage. In lung cancer cells, KEAP1 mutations lead to NRF2 deregulation and contribute to tumorigenesis. Researchers have been searching for an effective way of targeting this pathway in cancer cells to sensitize them to ferroptosis/radiation-inducing agents. They found that FSP1 is upregulated in KEAP1-mutant lung cancer cells, and its expression is associated with resistance to ferroptosis and radiotherapy. Coenzyme Q10- (CoQ) FSP1 signaling represents a potential target for overcoming resistance to ferroptosis and radiotherapy in KEAP1-mutant lung cancer cells.

“Currently, there are four major ferroptosis-defending systems, while NRF2 could directly control two of them, SLC7A11/GSH/GPX4 axis and CoQ/FSP1 axis.”

This study provides new insights into the role of target genes in the KEAP1-NRF2 pathway and how they contribute to cancer cells’ resistance to ferroptosis and radiotherapy. However, the mechanism by which KEAP1-NRF2 target genes mediate resistance to ferroptosis is not yet fully understood. Fortunately, the identification of FSP1 as a key target gene involved in this process opens up new therapeutic avenues for the treatment of lung cancer.

“Here, Pranavi Koppula and her colleagues’ study indicates that pharmacological targeting of CoQ-FSP1 signaling to overcome KEAP1 deficiency-induced radioresistance could be a potentially effective therapeutic strategy in treating KEAP1 mutant lung cancers.”

Click here to read the full research perspective published by Oncotarget

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Oncotarget is an open-access journal that publishes primarily oncology-focused research papers in a continuous publishing format. These papers are available at no cost to readers on Oncotarget.com. Open-access journals have the power to benefit humanity from the inside out by rapidly disseminating information that may be freely shared with researchers, colleagues, family, and friends around the world.

For media inquiries, please contact media@impactjournals.com.

Synergy of HDACi, PARPi and Chemotherapeutics Against Blood Cancer

Researchers investigated the efficacy of HDAC inhibitors in combination with PARP inhibitors and chemotherapeutic drugs in multiple blood cancer cell lines.

Synergy of HDACi, PARPi and Chemotherapeutics Against Blood Cancer
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Chromatin constitutes chromosomes in eukaryotic cells and comprises DNA and proteins. Chromosomes produce proteins and enzymes that are essential for cellular function and maintenance, including DNA repair. A critical process for DNA repair is poly(ADP-ribosyl)ation, or PARylation.

PARylation is triggered by poly(ADP ribose) polymerase (PARP) enzymes. When DNA becomes damaged, PARP enzymes bind to the damaged location in the cell. In cancer cells, however, this natural process can be counterproductive in respect to cancer treatment. PARylation can produce DNA repair mechanisms in cancer cells that can lead to cell death evasion and even drug resistance. Inhibiting PARylation may be a viable therapeutic strategy for cancer treatment.

HDAC Inhibitors

Histones, the main proteins that constitute chromatin, undergo post-translational modifications that regulate gene expression. Histone acetylation is an important epigenetic process that affects gene expression by relaxing the chromatin structure, making chromatin remodeling more feasible. Histone deacetylases (HDACs) are enzymes that can have the opposite effect. Histone deacetylation makes the chromatin more compact and difficult to remodel. The overexpression of HDAC has also been associated with tumorigenesis. Histone deacetylase inhibitors (HDACi) are a class of therapeutics that have shown promise in the treatment of hematologic malignancies (blood cancer) and solid tumors.

“Overexpression of HDACs has been associated with tumorigenesis by down-regulation of tumor suppressor genes [3, 4]; hence, HDAC inhibitors (HDACi) including vorinostat (SAHA), romidepsin (Rom), panobinostat (Pano) and belinostat have been approved by the United States Food and Drug Administration for the treatment of hematologic and other malignancies [5]. These inhibitors restore appropriate gene expression, resulting in induction of cell differentiation, cell cycle arrest and apoptosis [6].”

The Study

In a new study, researchers Benigno C. Valdez, Yago Nieto, Bin Yuan, David Murray, and Borje S. Andersson from the Department of Stem Cell Transplantation and Cellular Therapy at the University of Texas MD Anderson Cancer Center and the Cross Cancer Institute’s Department of Experimental Oncology at the University of Alberta investigate the efficacy of HDACi in combination with PARP inhibitors (PARPi) and chemotherapeutic drugs to treat hematologic cancer. On October 14, 2022, their research paper was published in Volume 13 of Oncotarget, entitled, “HDAC inhibitors suppress protein poly(ADP-ribosyl)ation and DNA repair protein levels and phosphorylation status in hematologic cancer cells: implications for their use in combination with PARP inhibitors and chemotherapeutic drugs.”

“Despite their preclinical efficacy, HDACi do not seem to be clinically highly effective as monotherapy, and potentially more effective anti-tumor activity is observed when they are combined with other anti-cancer drugs [79].”

Studies on the interactions of HDACi with PARPi in cancers of the blood are limited, especially when combined with chemotherapeutic agents. The researchers used a panel of hematologic cancer cell lines (acute myeloid leukemia, T-cell acute lymphoblastic leukemia, chronic myeloid leukemia, and multiple myeloma) and patient-derived cell samples to study the effect of HDACi (including SAHA (Vorinostat), panobinostat (Pano), romidepsin (Rom) and trichostatin A (TSA)) on PARylation. In addition, the team looked at the efficacy of HDACi combined with PARPi, including Olaparib (Ola) and niraparib (Npb), and with chemotherapeutic agents gemcitabine (Gem), busulfan (Bu) and melphalan (Mel).

Results

The researchers found that hematologic cancer cell lines and patient-derived cell samples exposed to various HDACi resulted in a significant caspase-independent inhibition of protein PARylation. HDACi-mediated inhibition of protein PARylation was mainly catalyzed by PARP1. These findings suggest that HDACi could potentially be used in combination with PARP inhibitors and chemotherapeutic drugs to treat blood cancers.

“Our results indicate that the anti-tumor efficacy of HDACi is partly due to down-regulation of PARylation, which negatively affects the status of DNA repair proteins. This repair inhibition, combined with the high levels of oxidative and DNA replication stress characteristic of cancer cells, could have conferred these hematologic cancer cells not only with a high sensitivity to HDACi but also with a heightened dependence on PARP and therefore with extreme sensitivity to combined HDACi/PARPi treatment and, by extension, to their combination with conventional DNA-damaging chemotherapeutic agents. The observed synergism of these drugs could have a major significance in improving treatment of these cancers.”

Conclusion

HDACi drugs can inhibit PARylation. The combination of HDACi-mediated inhibition of PARylation was complemented by PARPi and chemotherapeutic agents in multiple blood cancer cell lines. The efficacy of this combined treatment was superior to that of any single agent, supporting the further clinical development of HDACi in cancer therapy. These findings could potentially be used to improve the treatment of hematologic cancers.

“In conclusion, our results provide a molecular explanation for the HDACi-mediated inhibition of DNA repair in hematologic cancer cells and support the combinatorial application of HDACi, PARPi and chemotherapeutic agents for the treatment of hematologic malignancies.”

Click here to read the full research paper published by Oncotarget

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Oncotarget is an open-access journal that publishes primarily oncology-focused research papers in a continuous publishing format. These papers are available at no cost to readers on Oncotarget.com. Open-access journals have the power to benefit humanity from the inside out by rapidly disseminating information that may be freely shared with researchers, colleagues, family, and friends around the world.

For media inquiries, please contact media@impactjournals.com.

CRISPR Screens Identify Novel Targets for Personalized Cancer Therapy

In this trending new study, researchers used CRISPR-based genome-wide screens to identify genetic determinants of PARP10-mediated cellular survival.

CRISPR Screens Identify Novel Targets for Personalized Cancer Therapy
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The Trending With Impact series highlights Oncotarget publications attracting higher visibility among readers around the world online, in the news, and on social media—beyond normal readership levels. Look for future science news about the latest trending publications here, and at Oncotarget.com.

Genetic interactions involved in the survival of cancer cells are potential therapeutic targets in personalized cancer therapy. “Synthetic lethal” is a type of genetic interaction where the knockout of one gene can cause cell death but only in the presence of another dependent gene. Cancer researchers view synthetic lethality screening as a powerful tool in precision medicine.

“Identifying genetic susceptibilities based on PARP10 expression levels is thus potentially relevant for finding new targets for precision oncology.”

Poly-ADP-ribose polymerase 10, or PARP10, is a nuclear protein that is overexpressed in multiple cancers. Genetic susceptibilities based on PARP10 expression levels in an individual may be potential targets for personalized cancer therapy. In a new study, researchers Jude B. Khatib, Emily M. Schleicher, Lindsey M. Jackson, Ashna Dhoonmoon, George-Lucian Moldovan, and Claudia M. Nicolae, from the Department of Biochemistry and Molecular Biology at Penn State College of Medicine, used CRISPR-based, genome-wide genetic screens to identify potential synthetic lethality interactions with PARP10-overexpressing and -knockout cancer cells. On September 28, 2022, their research paper was published in Oncotarget and entitled, “Complementary CRISPR genome-wide genetic screens in PARP10-knockout and overexpressing cells identify synthetic interactions for PARP10-mediated cellular survival.”

“Here, we employed complementary CRISPR loss-of-function genome-wide screening to identify genes required for proliferation of PARP10-overexpressing and PARP10-knockout cells.”

The Study

To identify potential synthetic lethal targets, the researchers conducted a CRISPR-based, genome-wide genetic screen of both PARP10-overexpressing and PARP10-knockout tumorigenic and non-tumorigenic breast cells. The screen looked for genes that were required for cell proliferation in the presence of PARP10 overexpression or PARP10 knockout.

“Here, we performed a series of CRISPR genome-wide loss-of-function screens in isogenic control and PARP10-overexpressing or PARP10-knockout cell lines, to identify genetic determinants of PARP10-mediated cellular survival.”

In the PARP10 overexpressing cells, the top results from their CRISPR screen were validated with biological pathway enrichment analyses, using both KEGG and Gene Ontology databases. A functional interaction between ATM and PARP10 expression was found. ATM promoted cell proliferation in PARP10-overexpressing cells.

In the genome-wide CRISPR knockout screens, genes required for the viability of PARP10-knockout cells were identified. In the PARP10 knockout cells, the top results from their CRISPR screen were validated with biological pathway enrichment analyses, using both KEGG and Gene Ontology databases. They identified the CDK2-Cyclin E1 complex as a genetic determinant for the proliferation of PARP10-knockout cells.

“Our work identifies a network of functionally relevant PARP10 synthetic interactions, and reveals a set of factors which can potentially be targeted in personalized cancer therapy.”

Conclusion

The researchers identified several genes that were differentially required for cell proliferation in the presence of PARP10 overexpression or knockout. Some of these genes have been previously implicated in cancer, while others were novel candidate cancer targets. The identification of these potential synthetic lethal interactions provides new insights into the role of PARP10 in cancer and may be useful for precision oncology. This study highlights the importance of using complementary CRISPR-based screens to identify potential cancer targets.

“We found that DNA repair factors, including ATM, a master regulator of the DNA damage checkpoint response, are specifically promoting the proliferation of PARP10-overexpressing cells. Moreover, we identified a role for PARP10 in regulating ATM recruitment to stressed replication forks. Finally, we found that the CDK2-cyclin E1 complex is specifically required for the proliferation of PARP10-deficient cells. Our work reveals novel PARP10 genetic interactions of functional relevance and identifies a set of factors which can potentially be targeted in personalized cancer therapy.”

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How High Altitudes Influence HIF-1, Gastric Cancer & Patient Survival

In a new study, researchers evaluated the high altitude in Ecuador and how it may influence HIF-1 expression and the survival of Ecuadorian patients with gastric cancer.

El Panecillo hill in Quito, Ecuador
El Panecillo hill in Quito, Ecuador
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Altitude is considered any elevation above sea level. Higher altitude environments are known to influence various physiological processes in the human body, including those related to hypoxia-inducing factors (HIF), vitamin D, ultraviolet radiation, oxygen toxicity, and changes in pH. Researchers have suggested that altitude may even affect the development and progression of some diseases, including stomach/gastric cancer.

“Gastric cancer is the third leading cause of death in the world and is estimated to cause almost 15 million deaths by 2035 [2].”

Gastric Cancer & Altitude

The primary subtype of gastric cancer is gastric adenocarcinoma (GA). GA develops in the mucus-secreting cells that line the stomach (gastric epithelium). Higher incidence rates of GA have been found among populations living at high altitudes. High altitudes are notorious for low air pressure and decreased oxygen saturation levels. Decreases in oxygen (hypoxia) can activate the transcriptional regulator hypoxia-inducing factor-1 (HIF-1). HIF-1 is known to be upregulated in a variety of human cancers, including GA. The role of HIF-1 in GA pathogenesis and prognosis has not yet been fully understood.

“Gastric adenocarcinoma (GA) has a high incidence in Ecuador, in men it ranks third and in women it ranks fifth.”

There is a higher incidence of GA among people living in Ecuador. This is a country that straddles the equator yet, the altitude in Ecuador varies significantly across the country. For example, the altitude is 2,850 meters in the capital city of Quito (the second-highest capital city in the world). In Guayaquil (a coastal city in Ecuador) the altitude is only nine meters. These facts make Ecuador an optimal location for studying the effects of altitude on gastric adenocarcinoma.

“Ecuador has a varied altitude diversity and there is a differential incidence of cancer between populations living in the Andean or mountainous region when compared to coastal populations or living at low altitude.”

The Study

In a new retrospective study, researchers Edwin Cevallos Barrera, Edson Zangiacomi Martinez, Mariangela Ottoboni Brunaldi, Eduardo Antonio Donadi, Ajith Kumar Sankarankutty, Rafael Kemp, and José Sebastiao dos Santos from Universidad Central del Ecuador and University of São Paulo evaluated the high altitude in Ecuador and how it may influence HIF-1 expression and the survival of Ecuadorian patients with GA. Their research paper was published on September 14, 2022, in Oncotarget’s Volume 13, entitled, “Influence of high altitude on the expression of HIF-1 and on the prognosis of Ecuadorian patients with gastric adenocarcinoma.”

A total of 229 Ecuadorians were assessed in this study. The researchers included 155 cases of GA; 99 of the individuals with GA lived in the mountainous regions of Quito and Ambato, and 56 individuals lived in the coastal region of Guayaquil. (Controls accounted for 74 people; 25 from the coast and 49 from the mountains.) The team followed-up with all individuals in this study from 2005 to 2018 and collected blood and tissue samples. They performed immunohistochemistry and other analyses to evaluate HER2 and HIF-1 expression.

“Analyses were performed using Fisher’s exact and Breslow-Day tests for homogeneity and Kaplan-Meier curves and restricted median survival time ΔRMST.”

Results & Conclusion

After 10 years, median survival was significantly higher among GA patients living along the coast. In the GA samples, HIF-1 was observed in 66.1% of the coastal patients and in 43.4% of the mountainous patients. Positive HIF-1 expression was associated with improved survival among GA patients living in the mountains. Interestingly, in the control group (without GA), HIF-1 expression was observed in 95.9% of the mountainous samples and only 32% of the coastal samples. Their results showed that 89% of the control population exhibited gastritis.

The researchers were forthcoming about the limitations of this study. Differences in quantities and the male-to-female ratios within the GA and control coastal and mountainous groups may have influenced data. Despite these limitations, the researchers observed that coastal GA patients and individuals who expressed HIF-1 had a better prognosis. However, HIF-1 expression was only associated with better survival in the mountain region. These findings suggest that HIF-1 expression may be a protective factor against GA progression in people living at high altitudes.

“Concluding, this study suggests that HIF-1 has a differential expression pattern in gastric samples according to geographical features, being highly expressed even in non-carcinomatous cells (gastritis and normal mucosa) from individuals living in regions of high altitude, indicating that the gastric HIF-1 expression may be an adaptation of the individual to high altitudes.”

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Oncotarget is an open-access journal that publishes primarily oncology-focused research papers in a continuous publishing format. These papers are available at no cost to readers on Oncotarget.com. Open-access journals have the power to benefit humanity from the inside out by rapidly disseminating information that may be freely shared with researchers, colleagues, family, and friends around the world.

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Protein-Based Risk Model Predicts Esophageal Cancer Recurrence

Researchers developed a multi-protein expression-based risk model to predict recurrence-free survival for ESCC patients.

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Esophageal cancer is the sixth most common cause of death from cancer worldwide. The two main types of esophageal cancer are adenocarcinoma and esophageal squamous cell carcinoma (ESCC). ESCC arises from the cells lining the esophagus, and it is most common in areas of the world where tobacco use and alcohol consumption are high.

“Biomarkers to predict the risk of disease recurrence in Esophageal squamous cell carcinoma (ESCC) patients are urgently needed to improve treatment.”

Researchers Raghibul Hasan, Gunjan Srivastava, Akram Alyass, Rinu Sharma, Anoop Saraya, Tushar K. Chattopadhyay, Siddartha DattaGupta, Paul G. Walfish, Shyam S. Chauhan, and Ranju Ralhan from All India Institute of Medical Sciences, Mount Sinai Hospital Toronto, McMaster University, Guru Gobind Singh Indraprastha University, and the University of Toronto conducted a new study on the protein expression-based risk model they developed to predict recurrence-free survival for ESCC patients. On September 14, 2022, their research paper was published in Oncotarget’s Volume 13, and entitled, “Prediction of recurrence free survival for esophageal cancer patients using a protein signature based risk model.”

The Study

“Our study is important because: (i) it is based on changes in expression levels of the biomarker proteins in different subcellular compartments and is not limited to alterations in the overall protein expression levels; (ii) investigates the comprehensive clinical relevance of subcellular alterations in expression of multiple key components of Wnt pathway in the same ESCC patients’ cohort; (iii) correlates these findings with disease outcome and (iv) develops a Biomarker risk score for defining the risk of recurrence of ESCCs.”

Figure 1: Immunohistochemical analysis of Wnt protein in esophageal tissues.
Figure 1: Immunohistochemical analysis of Wnt protein in esophageal tissues.

The researchers aimed to develop and validate a panel of biomarkers with the potential to predict tumor recurrence in patients with ESCC, as well as to generate a risk model for clinical decision-making. This study enrolled 80 ESCC cases, 61 esophageal dysplastic tissues and 47 normal tissues. A multi-protein signature was generated from microarray data using the Cox proportional hazard model which was then internally validated on an independent set of samples by immunohistochemistry. The researchers demonstrated that a panel of four biomarkers (cytoplasmic β-catenin, nuclear c-Myc, nuclear DVL and membrane α-catenin) constituted the prognostic molecular signature for ESCC patients. They found that this protein signature could predict disease recurrence in patients with ESCC.

“Our panel of biomarkers predicted disease recurrence more effectively as compared to individual biomarkers analyzed in this study and demonstrated the strong predictive power of this panel of biomarkers for ESCC patients.”

Conclusion

The research team found that a panel of four biomarkers could predict disease recurrence in patients with ESCC. Furthermore, they showed that this protein signature could be used to stratify patients into high- and low-risk groups. This study provides valuable insights into the role of these proteins in the development and progression of esophageal cancer. The development of this risk model may help to tailor treatment and follow-up strategies for patients with ESCC.

“In conclusion, integrated analysis of expression of the panel of 4 proteins in ESCC patients has allowed us to validate the robustness of our biomarker panel in stratification of patients at high or low risk of disease recurrence. This risk classifier has the potential to identify the high risk patients for more rigorous personalized treatment and the low risk patients may be spared from the harmful side effects of toxic therapy as well reduce the burden on health care providers. The findings of our study set the foundations for external validation of the prognostic signature as a step forward in translation of this panel of protein markers for ESCC patients and establish their clinical relevance for larger worldwide application in future studies.”

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Oncotarget is an open-access journal that publishes primarily oncology-focused research papers in a continuous publishing format. These papers are available at no cost to readers on Oncotarget.com. Open-access journals have the power to benefit humanity from the inside out by rapidly disseminating information that may be freely shared with researchers, colleagues, family, and friends around the world.

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Immunotherapy Response Predicted by Machine Learning & Gut Microbiomes

Researchers investigated common gut microbiome features of response among immunotherapy patients with different advanced-stage cancers.

Machine Learning and Gut Microbiomes Predict Immunotherapy Response
Illustration of a gut microbiome
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Immunotherapy has become a powerful breakthrough in cancer treatment, however, 50% of patients do not respond to immunotherapy. What internal or external features inhibit or confer patient or tumor response to immune system-harnessing therapeutics? These patient/tumor features that impact responsiveness to immunotherapy have yet to be fully elucidated.

“Increasing evidence has emerged that gut microbial communities help shape the host immune system [911].”

The Gut Microbiome

The gut microbiome is the collection of all microbes living in the gastrointestinal tract. A growing body of evidence indicates that the gut microbiome is an important component of the human immune system. This evidence has prompted researchers to hypothesize that the gut microbiome may play a role in immunotherapy response. It has since become a focal point in immunotherapy research and also has the potential to serve as a biomarker for immunotherapy response.

Researchers previously found evidence that specific gut bacteria can influence immunotherapy outcomes by modulating immune responses in patients with melanoma, non–small cell lung cancer and renal cell cancer. (“Treatment responders generally exhibit increased gut microbial community diversity and are enriched in certain bacterial taxa including Akkermansia and Bifidobacterium [1619].”) While this is important, it is unclear whether these response signals are generalizable across different tumor types, geographical variations in the microbiome or sequencing platforms and analysis methodologies. Identifying microbiome features associated with immunotherapy response regardless of the type of cancer or where it started in the body may be the next step toward improving immunotherapy outcomes in cancer patients.

The Study

In a new study published in Oncotarget, Hai Liang, Jay-Hyun Jo, Zhiwei Zhang, Margaret A. MacGibeny, Jungmin Han, Diana M. Proctor, Monica E. Taylor, You Che, Paul Juneau, Andrea B. Apolo, John A. McCulloch, Diwakar Davar, Hassane M. Zarour, Amiran K. Dzutsev, Isaac Brownell, Giorgio Trinchieri, James L. Gulley, and Heidi H. Kong, from the National Institutes of Health LibraryNational Cancer Institute (NCI)National Human Genome Research InstituteWest Virginia UniversityZimmerman Associates Inc., and the University of Pittsburgh, used machine learning models to analyze gut microbiomes and predict patient response to immunotherapy. On July 19, 2022, the researchers published their paper in Oncotarget’s Volume 13, entitled, “Predicting cancer immunotherapy response from gut microbiomes using machine learning models.”

To find common gut microbiome features of response to immunotherapy, a tumor-agnostic and geographically limited (U.S. patients only) approach was used in this study. The researchers’ discovery cohort included 16 patients with nine different advanced-stage cancers who were enrolled in NCI immunotherapy trials (the NCI cohort). Patient samples and 16S rRNA gene sequencing data were collected. Patients who positively responded to immunotherapies (responders) and those who did not (non-responders) were categorized. The researchers used uni- and multivariate analyses to identify common microbiome features and complex microbial community interactions. 

Common microbiome features and immunotherapy response signals in the discovery cohort were further validated with larger datasets. Three previously published 16S rRNA gene sequencing datasets from melanoma patients were added to a combined dataset. This combined dataset was used to validate the NCI cohort results in a meta-analysis. Data from all four studies were used in statistical analyses and machine learning models aimed to predict immunotherapy response.

“Using the combined dataset, we trained and validated models with machine learning algorithms to predict patients’ clinical responses, followed by cross-sequencing-platform validation using shotgun metagenomic sequencing data.”

The Results

“Results suggest baseline gut microbiome features may be predictive of clinical outcomes in oncology patients on immunotherapies, and some of these features may be generalizable across different tumor types, patient cohorts, and sequencing platforms.”

The researchers found that the gut microbiome composition of responders to immunotherapy was different from that of non-responders. Several species of bacteria were differentially abundant between responders and non-responders in the NCI cohort, and some were also consistent with results from the meta-analysis. Hierarchical clustering showed a higher immunotherapy response rate among patients with enriched bacteria in the Firmicutes phylum and a lower response rate among patients enriched in the Bacteroidetes phylum at baseline. Machine learning models using microbiome features and immunotherapy response signals found in this study demonstrated a favorable prediction accuracy with the highest AUC (area under the curve) value of around 0.75.

Conclusion

“In conclusion, analyses of our cohort and the combined microbiome dataset have provided a robust assessment of immunotherapy patients’ gut microbiomes.”

Researchers used a tumor-agnostic approach to find common gut microbiome features of response to immunotherapy in cancer patients. The machine learning models developed in this study were able to demonstrate a favorable prediction accuracy of 75% at best. These results suggest that the gut microbiome may be predictive of immunotherapy response in cancer patients and that some of these features may be generalizable across different tumor types, patient cohorts, and sequencing platforms. These findings suggest that the gut microbiome is a promising biomarker for immunotherapy response. However, more research is needed to validate these findings in larger and more diverse patient populations.

“Results suggest baseline gut microbiome features may be predictive of clinical outcomes in oncology patients on immunotherapies, and some of these features may be generalizable across different tumor types, patient cohorts, and sequencing platforms. Findings demonstrate how machine learning models can reveal microbiome-immunotherapy interactions that may ultimately improve cancer patient outcomes.”

Click here to read the full research paper published by Oncotarget

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Oncotarget is an open-access journal that publishes primarily oncology-focused research papers in a continuous publishing format. These papers are available at no cost to readers on Oncotarget.com. Open-access journals have the power to benefit humanity from the inside out by rapidly disseminating information that may be freely shared with researchers, colleagues, family, and friends around the world.

For media inquiries, please contact media@impactjournals.com.