> For the complete documentation index, see [llms.txt](https://www.brexatlas.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.brexatlas.org/bre-001/bre-002.md). # BRE 002 ## Finding the Best Frequency for Cancer Treatment **Clinical Cancer Names:** Glioma, Glioblastoma, Ovarian Carcinoma **Common Cancer Names:** Brain Cancer and Ovarian Cancer ## Source Porat, Y., Giladi, M., Schneiderman, R. S., Blat, R., Shteingauz, A., Zeevi, E., Munster, M., Voloshin, T., Kaynan, N., Tal, O., Kirson, E. D., Weinberg, U., & Palti, Y. (2017). *Determining the Optimal Inhibitory Frequency for Cancerous Cells Using Tumor Treating Fields (TTFields).* *Journal of Visualized Experiments*, (123), e55820. *** ## BRE-002 Scoring Section **BRS Score**\ **BRS:** 8.4 / 10\ **STEMD:** S9 / T8 / E8 / M8 / D9\ **External Evidence Level:** Strong in-vitro frequency-optimization evidence ### Score Interpretation BRE-002 receives a strong score because it directly supports one of BREXAtlas’s core claims: different cancer types may respond optimally to different TTFields frequencies rather than one universal frequency. It includes melanoma, breast cancer, and glioma models across 100–200 kHz, making it highly valuable for the Frequency Specificity Index. *** ## Entry Summary If BRE-001 asked whether electric fields can interfere with cancer cell division, BRE-002 asks a different question: **What frequency works best?** This study focused on frequency optimization. Rather than testing whether Tumor Treating Fields work, researchers investigated how changing frequency affected treatment response. The findings support one of the central concepts of BREXAtlas: **The most effective frequency may depend on the cancer being treated.** This means that bioelectric treatment may need to be tuned to the biology of specific cancers rather than applying one universal frequency to every tumor. *** ## Question This BRE Helps Answer **Is there one frequency that works for every cancer?** ### What BREXAtlas found: This study found no evidence that a single frequency is automatically optimal for all cancers. Instead, researchers tested multiple frequencies and observed that cancer cell inhibition changed depending on the frequency used. The strongest responses occurred near specific frequency ranges. *** ## Why does frequency matter? Imagine a radio. Turning the dial slightly changes what station you hear. BRE-002 suggests cancer cells may respond similarly. A small change in frequency may produce a different biological response. Some frequencies may have little effect. Other frequencies may produce substantial inhibition. The study therefore supports frequency optimization as a necessary part of bioelectric oncology. *** ## Can treatment effectiveness increase simply by adjusting frequency? ### What BREXAtlas found: Yes. The study demonstrated that treatment effectiveness varied across tested frequencies. Response generally became stronger as researchers approached the optimal frequency for a given cell line and decreased when moving away from that frequency. This suggests that treatment success may depend not only on using electric fields, but also on using the correct electric field. *** ## Cell Lines Cataloged in This Entry ### Brain Cancer (Glioma / Glioblastoma) * F98 * U-87 MG ### Ovarian Cancer * A2780 * OVCAR-3 *** ## Treatment Parameters | Parameter | Value | | ------------------------ | -------------------------- | | Treatment Type | Tumor Treating Fields | | Frequency Range Tested | 100–500 kHz | | Exposure Duration | 72 hours | | Field Intensities Tested | 1.0, 1.3, and 1.7 V/cm RMS | | Replicates | Six or more per frequency | *** ## Frequency Findings ### Optimal Frequencies Identified | Cell Line | Cancer Type | Optimal Frequency | | --------- | -------------- | ----------------- | | A2780 | Ovarian Cancer | 200 kHz | | OVCAR-3 | Ovarian Cancer | 200 kHz | | F98 | Brain Cancer | 200 kHz | | U-87 MG | Brain Cancer | 200 kHz | *** ## What BREXAtlas Found BRE-002 strengthens the frequency-specific observations first introduced in BRE-001. The study demonstrates that: * Frequency can influence treatment response. * Frequency can be measured experimentally. * Frequency optimization is reproducible. * Response changes as frequency changes. * TTFields treatment can be systematically tuned. BREXAtlas classifies this study as one of the earliest optimization-focused investigations in bioelectric oncology. *** ## What Makes This Study Important? Many cancer treatments focus on finding the correct drug. This study focused on finding the correct frequency. That distinction is important. It shifts part of the treatment discussion from chemistry to physics. The findings suggest that future bioelectric therapies may require frequency selection in the same way medication therapies require dose selection. *** ## Questions Raised for Future Research ### Can frequency be predicted before treatment begins? This remains unanswered. Future studies may determine whether cell size, tissue type, genetics, electrical properties, or other biological features can predict optimal frequency. ### Do cancers from the same tissue share similar frequencies? This study provides early evidence that they might. Both ovarian cancer cell lines responded optimally at 200 kHz. Both brain cancer cell lines also responded optimally at 200 kHz. However, larger studies are needed before broader conclusions can be drawn. ### Can a mathematical model predict frequency response? BREXAtlas identifies this as one of the most important unanswered questions emerging from this study. If frequency response becomes predictable, future bioelectric treatment systems could potentially recommend frequencies automatically based on tumor characteristics. *** ## Public Source Validation Public scientific databases classify this publication as a methodology and optimization study for Tumor Treating Fields. The study is widely cited within the TTFields literature because it provides a reproducible process for identifying optimal frequencies. BREXAtlas interpretation aligns with the published findings and does not introduce unsupported claims. The added value of BREXAtlas is organization and integration with other frequency-response studies. *** ## Connections to Other BRE Entries ### Connected to BRE-001 **Why this connection matters:** BRE-001 established that different cancers may respond differently to electric fields. BRE-002 expands that finding by testing how frequency affects treatment effectiveness. Together, BRE-001 and BRE-002 form the foundation of the BREXAtlas frequency-response framework. **Recommended Reading:**\ Read BRE-001 before BRE-002. *** ### Connected to Future Ovarian Cancer Entries BRE-002 provides one of the earliest ovarian cancer frequency records in the encyclopedia. Future ovarian cancer entries should be compared against: * A2780 * OVCAR-3 to determine whether 200 kHz remains consistently supported. *** ### Connected to Future Predictive Modeling Entries BRE-002 contributes directly to future BREXAtlas prediction models because it establishes measurable relationships between: * Frequency * Cell line * Tissue type * Treatment response *** ## Research Gaps Identified ### RG-006: Frequency Prediction Gap Can optimal frequencies be predicted rather than experimentally discovered? ### RG-007: Frequency Stability Gap Do frequencies remain stable across laboratories, conditions, and patient-derived samples? ### RG-008: Tissue Clustering Gap Do cancers from the same tissue naturally cluster around similar frequencies? ### RG-009: Mathematical Modeling Gap Can frequency-response curves be modeled and used for treatment planning? ### RG-010: Personalized Frequency Gap Could future treatments assign frequencies individually to each patient's tumor? *** ## Why This Entry Matters BRE-001 introduced the possibility that cancer cells possess electrical vulnerabilities. BRE-002 introduces the possibility that those vulnerabilities can be tuned and optimized. For researchers, this study strengthens the scientific basis for frequency-specific treatment. For patients and families, the key takeaway is simple: Not all electric-field treatments are the same. The frequency used may be just as important as the treatment itself. *** ## Entry Conclusion BRE-002 is the first dedicated frequency-optimization entry in the BREXAtlas Encyclopedia. It provides evidence that cancer response varies according to frequency and that identifying optimal frequencies may become one of the most important challenges in bioelectric oncology. Together with BRE-001, this study establishes one of the central themes of the encyclopedia: **Cancer cells may not only be biologically different—they may also be electrically different.** --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://www.brexatlas.org/bre-001/bre-002.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.