HUMAN PRACTICES

Phase I Human Practices

During Phase I, we conducted 15 stakeholder interviews with physicians, patients, researchers, ethicists, executives of advocacy programs, and corporate directors. To integrate their responses, we learned the importance of:

  • Lack of Treatments for Orphan Diseases: Current treatment options in glioblastoma are sparse and the drug development pipeline is slow.
  • The FDA Approval Process – A Double-Edged Sword: Although the long drug approval process is necessary to ensure that new drugs are effective and safe, some stakeholders are frustrated that patients are suffering while waiting for a drug that already exists.
  • Mixed Perspectives on Organoids for in vitro Drug Screening: Although some physicians are skeptical about making patient treatment decisions solely based on organoid drug screening, organoid technologies can be useful as a preclinical drug testing tool for mutation-specific therapeutics.
  • Sex Differences in GBM: Signaling pathways that are affected in glioma can vary between male and female patients; as such, the treatment options that a physician pursues must be cognizant of these differences.
  • Clinical Trial Initiatives/Diversity: This ensures that our system is able to identify compounds that are effective and safe for individuals, regardless of any genotypic or phenotypic differences. On the other hand, utilizing a diverse sample would allow us to identify how drug responses might vary across different groups, allowing therapeutics to be designed and applied in a more targeted manner.
  • Patient Privacy and Ownership of Samples: The team learned about the importance of differentiating between de-identification and anonymization of samples. In the former, identifying information is removed without eliminating access to medically relevant information. In the latter, all information about the source of the tissue sample is removed.
  • Emotional Impacts of Glioma: Diagnosis of brain cancer are life-changing events, and patients are forced to quickly adjust to new realities in the treatment period.
  • Patient Advocacy and Education: Through our interviews with organizations like the American Brain Tumor Association (ABTA) and Pediatric Brain Tumor Foundation (PBTF), the team learned more about the vital role that patient advocacy organizations play in supporting patients through the overall treatment process.


See our 2021 Human Practices Wiki Page for more details.

Phase II Human Practices

Our human practice interviews with stakeholders such as Dr. Henry Friedman from Phase I motivated us to shift the direction of our project from a generalized glioma system to an IDH1-specific glioma drug screening platform.

From our Phase I interviews with Professor Sara Katsanis and Dr. Katherine Peters, we also learned about the delicate balance between patient privacy and diversity. In Phase II of our project, we were motivated to incorporate their feedback by investigating how our project impacts equitable health outcomes for individuals belonging to demographics underrepresented in glioma research.

Mutation-specific System

After interviewing key stakeholders such as neuro-oncologist Dr. Henry Friedman, our team questioned whether our system was able to adequately model gliomas, which are a broad category of tumors affecting the brain and spinal cord. After learning about the concerns several stakeholders had about trusting a generalized organoid-drug screening platform, we decided to shift our project to target a specific glioma mutation. Refining our project to reflect a particular subset of this disease allowed us to create a more accurate model to be used as a drug screening platform.

Dr. Friedman introduced the IDH1 mutation to our group, mentioning its prevalence among secondary gliomas. After our human practices interviews, we fundamentally altered our original project, shifting from a glioma-wide platform to a system that focuses on the specific, but widely occurring IDH1 mutation. Listening to the feedback from our stakeholders allowed us to generate a drug screening platform that will provide a more accurate drug response to potential IDH1-specific glioma therapeutics, increasing its reliability and credibility.

Stakeholders

Our continued engagement with stakeholders – neurooncologists, cancer patients, drug developers, and ethicists – sparked our investigation of sociodemographic, especially sex-based dimorphisms in gliomas.

Dr. Katherine Peters, MD PhD FAAN

Associate Professor - Preston Robert Tisch Brain Tumor Center (PRTBTC), Duke University

Our discussions with Dr. Peters revolved around factors that implicate glioma prognosis, most notably the sexually dimorphic biomarkers IDH1 and IDH2, which consequently became the focus of NODES. As Dr. Peters researches the cognitive and physical function of glioma patients and their qualities of life, she has witnessed first-hand how differences in male-female cell signaling pathways influence patient phenotype and treatment responsiveness. Dr. Peters stressed that “testing with tissue samples from only one demographic” – as is current industry standard practice with Caucasian, middle-aged, male cell lines – causes researchers to “overlook” key factors that impact drug efficacy for the glioma patient population at large.

Professor Sara Katsanis

Assistant Professor - Feinberg School of Medicine, Northwestern University

Our conversation with Professor Katsanis provided us insight into her background as an ethicist researching genetic testing technologies. With respect to sex and racial inequity in glioma research, Professor Katsanis recommended the “de-identification” but “non-anonymization” of patient-derived samples in biobanks. Such “collective phenotypic data” would prove “key to understanding the connection between diverse genotypes and disease states.” Professor Katsanis additionally probed the ethicality of our project’s intersection with precision medicine, as, historically, the emerging field’s gleaning of information from “only a specific subgroup of a population” has advanced misinformation surrounding potential drug and treatment efficacy for underrepresented patient demographics. Consequently, the human practices component of NODES advocates against the generalization of “n-of-one” clinical trials and for the employment of globally representative patient-derived cell lines in cancer research.

Most Frequently Cited Glioma Cell Lines in Research

The first step of integrating stakeholder feedback into NODES involved further research of the demographic characteristics of the most cited cell lines in current glioma research. Through this process, we aim to comprehend the extent of the field’s marginalization of female and minority individuals.

Cell line U87MG [1] [2] T98G [3] [4] A172 [5] [6]
Sex Male Male Male
Ethnicity 72.18% Northern European, 23.21% Southern European 60.81% Southern European, 6.22% Northern European 68.98% Northern European, 27.77% Southern European
Age - 61 yo 53 yo


We learned that while the majority of cells “lose a number of innate characteristics or acquire new ones” during prolonged cultivation, U87MG, T98G, and A172 supposedly retain representativeness of the tumor origin, thus largely explaining their prevalence in lab-settings. U87MG, T98G, and A172 additionally “manifest high proliferative activity,” due to 95%-98% of their cells testing “positive for the proliferation marker Ki67 as identified by flow cytometry.” The cell lines doubling time falling between 26 and 48 hours proves convenient for the fast-paced nature of cell culture and transfection experimentation [7]. Finally, U87MG, T98G, and A172 are positive for the tumor progression and migration marker Thrombospondin-1 expression, therefore suggesting that the cell lines “exhibit the typical expression profile for mesenchymal and growth factor genes.”[7]

U87MG, T98G, and A172’s ease of use has likely permitted glioma researchers to eschew obvious demographic homogeneity, and even, in the case of U87MG, tumor inauthenticity. Indeed, the U87MG cell line as commercialized by the ATCC and CLS differs in its genetic profile from the original donor’s, causing a lack of standardization across the cell line’s “1700 entries in PubMed and 65000 citations in the ISI Web of Science.” [8] NODES calls for glioma researchers to employ accessible, commercially available cell lines that are both tumor-representative and display the sex and racial-specific biomarkers characteristic of the disease.

Dimorphisms

The NODES project team continued to incorporate stakeholder feedback by exploring the specific dimorphic mutations and promoter methylations that cause glioma to lend itself to precision medicine by “requiring an individualized approach to management considering the sex of the patient.” [9]

While the incidence of glioma is 1.6 times higher in men than in women, approximately 125,000 women worldwide are diagnosed with the disease annually, often experiencing “larger tumor size and areas of necrosis” than their male counterparts [9] Consequently, glioma researchers cannot employ the often-cited incidence rate as a rationalization for providing women with subpar non-specific therapeutics.

Indeed, sexual dimorphisms in glioma are impossible not to acknowledge, as discrepancies in symptom expression facilitate their recognition even outside of the scientific community. For example, while “women report a higher intensity and frequency of fatigue,” men fall victim to seizures at nearly two times the rate [9]. Broadly, such differences exist because both sex hormones like estrogen and testosterone are permitted across the blood-brain barrier; in the brain, estrogen plays a role in preventing neuronal death while testosterone activates the glioma-proliferative AR signaling pathway [9].

More specifically, the NODES project team investigated the sexually and racially dimorphic p53 and IDH1/2 mutations, as well as MGMT promoter methylation. “Tumor suppressor p53 is the chief operating officer of cancer defense,” as “wild-type p53 protein is amassed in response to cellular stress,” thus preventing the “conveyance of genetic damage into future generations of cells” [10]. During glioma tumorigenesis, p53 undergoes loss of function most notably by p53 SNP72Pro, a change of the amino acid Arginine (CGC) to Proline (CCC). p53 SNP72Pro is “less capable of eliminating cells with DNA damage,” and is “more frequent in Chinese and African-American patients than Caucasians” [10]. Indeed, p53 mutations are also sexually dimorphic, as X-linked O-GlcNAc Transferase (OGT) “dramatically modifies p53 introducing a glycosylation event that has been linked to reduced proteasomal degradation of p53,” therefore affording women a glioma survival advantage. However, “p53 transcriptional activity declined more slowly with age in males compared with females” consequently emphasizing the destructive effect of losing estrogen’s neuroprotection following menopause [10].

Our NODES project team chose to focus our cell line work on “mutations in isocitrate dehydrogenase 1 & 2 (IDH1/2),” which recent studies hypothesize may exhibit a “sex-specific survival benefit for men” diagnosed with glioma. IDH 1/2 mutations are characterized as pro-oncogenic, as they oftentimes cause the “aberrant accumulation” of D-2-hydroxyglutarate (D-2-HG), an oncometabolite [9].

Analyzing the p53 and IDH1/2 mutations in conjunction catalyzed our inquiry into the sex-based frequency of glioma mutations, a search that revealed that females glioma patients were significantly more affected, with the median mutation rate among females of 56.5 , compared to 49 in males [18]. MGMT promoter methylation proves of paramount importance in glioma treatment efficacy, as “the O(6)-methylguanine-DNA methyltransferase (MGMT) gene codes for a DNA repair enzyme that – if active – can counteract the effects of chemotherapy [11]." Indeed, MGMT “removes alkyl groups from the O6 position of guanine, an important site of DNA alkylation,” thus preventing “chemotherapy-induced alkylation at this site” from triggering “cytotoxicity and apoptosis [11]." 80% of female glioma patients present with a hypermethylated MGMT promoter compared to only 27% of men [9]. This sexual dimorphism is currently being leveraged in clinical trial selection and stratification, as researchers seek treatments for (mostly) men failing to respond to typical therapeutic programs.

Recommended Cell Lines
Cell line U87MG [1] [2] T98G [3] [4]
Sex Female Female
Mutation Mutated p53 Methylated MGMT & Mutated IDH R132H
Ethnicity 759.47% Northern European, 38.27% Southern European -
Age 60 yo 49 yo


The two cell lines in the table above are both from underrepresented groups and are related to at least one of the specific dimorphisms implicated in glioma therapeutic outcomes. LN-299 (ATCC) is a glioma cell line derived from a female patient with a mutated p53.

BT54 is also a female-derived cell line and has a methylated MGMT promoter and IDH mutant R123H. This promoter’s methylation silences the MGMT gene and has been identified as a favorable outcome in GBM patients [11]. We propose this cell line be incorporated into research studies due to the experimental support surrounding its dimorphisms’ connection to improvements in glioma prognosis. However, it has not been experimentally determined whether or not improvements in prognosis in patients with MGMT methylation can be attributed to the methylation only or rather to unexplored dimorphisms that coexist with MGMT methylation [11]. Extensive research using these cell lines may discourage research that aims to better understand the native tumor microenvironment and the other dimorphisms and mutations that have led to differences in prognosis. Thus, glioma research must be conscious to include cell lines with more diverse origins and dimorphisms while refraining from extensively researching with only a few of these cell lines.

Ethics of Precision Medicine

After reflecting upon our stakeholders’ ethical anxieties surrounding the widespread adoption of precision medicine, the NODES project team worked to discern the avenues through which pharmacogenomics exacerbates and alleviates existing disparities in healthcare.

Precision medicine, specifically pharmacogenomics (PGX), was first pioneered in the high-grade glioma space to problem-solve “individuals varying in their response to many drugs;” “in the case of nonresponders, effective treatment is delayed,” and “with regard to adverse effects, some individuals suffer serious and even life-threatening complications [16]. In cancer diagnostics and therapeutics more broadly, precision medicine attempts to “individualize care” by accounting for the “differences in genetics, lifestyle, and environment” that implicate a patient's unique response to a specific disease [16].

Some bioethicists have deemed precision medicine inequitable, due to the input-output problem, eurocentric prioritization of diseases, prohibitive economic barriers to treatment, and de-emphasis of non-genetic factors in perpetuating health disparities. The input-output problem describes the attempted application of “pharmacogenomic algorithms that guide drug dosing and selection” derived from “well-studied populations” to medically marginalized individuals with “significantly different background genetic variations [17] ." Indeed, 75% of studies published by the National lHuman Genome Research Institute involved only patients of European descent [17]. Bioethicists have also observed that, as leading causes of death in developing nations are relatively rare in low- and middle-income countries (LMICs), precision medicine research dollars are failing to be allocated to diseases with primarily non-white and low-income patients [17]. Another economic complication of precision medicine comes in the form of the high sticker price of “laboratory tests that inform personalization [17]." One example is next generation sequencing, which is unlikely to be covered by either private or nationalized health insurance plans due to “unestablished efficacy [17]." While PGX testing “may have the potential to decrease overall costs at the level of the healthcare system,” individual patients will likely pay out-of-pocket for “medications with high direct costs compared with the standard therapy [17]." Finally, a myopic focus on the promise of precision medicine may obscure the cultural and socioeconomic disparities injustices that ultimately ramify to perpetuate disease.

Other bioethicists, however, believe that precision medicine will alleviate disparities in health care outcomes, as PGX researchers “may identify the genetic variants that contribute to recognized differences in drug responses among racial and ethnic groups [17]." This disparity warrants further discussion of stakeholders on different aspects of bioethics.

References

  1. U-87 MG. ATCC. (n.d.). Retrieved October 10, 2022, from https://www.atcc.org/products/htb-14
  2. Cellosaurus. Cellosaurus cell line U-87MG ATCC (CVCL_0022). (n.d.). Retrieved October 10, 2022, from https://www.cellosaurus.org/CVCL_0022
  3. T98G [T98-G] - CRL-1690 | ATCC. (n.d.). Retrieved October 11, 2022, from https://www.atcc.org/products/crl-1690
  4. Cellosaurus. Cellosaurus cell line T98G (CVCL_0556). (n.d.). Retrieved October 10, 2022, from https://www.cellosaurus.org/CVCL_0556
  5. A-172 [A172]. ATCC. (n.d.). Retrieved October 10, 2022, from https://www.atcc.org/products/crl-1620
  6. Cellosaurus. Cellosaurus cell line A-172 (CVCL_0131). (n.d.). Retrieved October 10, 2022, from https://www.cellosaurus.org/CVCL_0131
  7. Kiseleva, L.N., Kartashev, A.V., Vartanyan, N.L. et al. A172 and T98G cell lines characteristics. Cell Tiss. Biol. 10, 341–348 (2016). https://doi.org/10.1134/S1990519X16050072
  8. Allen, M., Bjerke, M., Edlund, H., Nelander, S., & Westermark, B. (2016). Origin of the U87MG glioma cell line: Good news and bad news. Science translational medicine, 8(354), 354re3. https://doi.org/10.1126/scitranslmed.aaf6853
  9. Carrano, A., Juarez, J. J., Incontri, D., Ibarra, A., & Guerrero Cazares, H. (2021). Sex-Specific Differences in Glioblastoma. Cells, 10(7), 1783. https://doi.org/10.3390/cells10071783
  10. Haupt, S., & Haupt, Y. (2021). Cancer and Tumour Suppressor p53 Encounters at the Juncture of Sex Disparity. Frontiers in genetics, 12, 632719. https://doi.org/10.3389/fgene.2021.632719
  11. Riemenschneider, M. J., Hegi, M. E., & Reifenberger, G. (2010). MGMT promoter methylation in malignant gliomas. Targeted oncology, 5(3), 161–165. https://doi.org/10.1007/s11523-010-0153-6
  12. LN-229. ATCC. (n.d.). Retrieved October 10, 2022, from https://www.atcc.org/products/crl-2611
  13. Cellosaurus. Cellosaurus cell line LN-229 (CVCL_0393). (n.d.). Retrieved October 10, 2022, from https://www.cellosaurus.org/CVCL_0393
  14. BT54. ATCC. (n.d.). Retrieved October 10, 2022, from https://www.atcc.org/products/crl-3416
  15. Cellosaurus. Cellosaurus cell line BT054 (CVCL_N707). Retrieved October 10, 2022, from https://www.cellosaurus.org/CVCL_N707
  16. Korngiebel, D. M., Thummel, K. E., & Burke, W. (2017). Implementing Precision Medicine: The Ethical Challenges. Trends in pharmacological sciences, 38(1), 8–14. https://doi.org/10.1016/j.tips.2016.11.007
  17. Brothers, K. B., & Rothstein, M. A. (2015). Ethical, legal and social implications of incorporating personalized medicine into healthcare. Personalized medicine, 12(1), 43–51. https://doi.org/10.2217/pme.14.65
  18. Zhang, H., Liao, J., & Li, X. (2019). Sex difference of mutation clonality in diffuse glioma evolution. Neuro-Oncology, 21(2), 201-213. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6374767/