#Peptide Therapy vs. Traditional Treatments

[atlanticsportsmed12]

Peptide Therapy vs. Traditional Treatments: Pros and Cons

Introduction:

In the realm of modern medicine, the debate between peptide therapy and traditional treatments often arises. Both approaches have their own set of advantages and drawbacks, making it essential for patients to understand the differences. In this blog, we'll delve into the pros and cons of peptide therapy compared to traditional treatments, offering valuable insights for informed decision-making.

Pros of Peptide Therapy:

Targeted Approach: Peptide therapy often involves the use of specific peptides that target particular receptors or pathways in the body. This targeted approach can result in more precise and effective treatment outcomes, especially for conditions with complex underlying mechanisms.

Fewer Side Effects: Peptides are naturally occurring molecules in the body and are generally well-tolerated. Compared to some traditional treatments that may cause adverse reactions or long-term complications, peptide therapy often boasts a lower risk of side effects.

Potential for Personalization: Peptide therapy can be customized based on individual needs and genetic factors. This personalized approach may lead to better treatment outcomes, as dosages and formulations can be tailored to suit each patient's unique physiology.

Stimulating Natural Processes: Many peptides work by mimicking or enhancing natural physiological processes in the body. This means that instead of merely suppressing symptoms, peptide therapy may help restore balance and promote healing from within.

Cons of Peptide Therapy:

Limited Availability: Compared to conventional medications, certain peptides used in therapy may have limited availability or may be more challenging to access. This could pose logistical challenges for patients, especially if they reside in areas where peptide therapy is not widely offered.

Cost Considerations: Peptide therapy, particularly when customized or utilizing novel peptides, can be expensive. Affordability may be a significant barrier for some individuals, especially if insurance coverage is limited or unavailable for these treatments.

Research and Regulation: While peptide therapy holds promise, there is still much to learn about its long-term efficacy and safety. Additionally, regulatory standards for peptide-based treatments may vary between regions, leading to inconsistencies in quality control and oversight.

Administration Route: Depending on the specific peptide and condition being treated, administration of peptide therapy may require injections, which can be daunting for some patients. Alternative delivery methods such as oral or nasal formulations are being explored but may not be as effective for certain peptides.

Conclusion:In weighing the pros and cons of peptide therapy versus traditional treatments, patients should consult with healthcare professionals to determine the most suitable approach for their individual needs. While peptide therapy offers targeted and potentially safer alternatives to conventional treatments, considerations such as availability, cost, and administration route must be carefully evaluated. As research in peptide therapy continues to evolve, it holds promise as a valuable addition to the medical armamentarium, offering new avenues for addressing a wide range of health conditions.

[dranshulgupta]

Functional vs integrative medicine

Healthcare sector has undergone drastic advancements in the past decade. Alternative forms of medicinal practices have started taking their well-deserved front row spaces among patients. Of these various methods of time-proven alternative therapies, Functional Medicine and Integrative Medicine approach are being highly regarded in the world of medical care.

While both Integrative and Functional Medicine follow a similar holistic method to treat a patient, there are a few distinctive features that make each of these unique. - Functional Medicine Doctor Los Angeles

  Functional medicine -

Functional medicine follows a system-based approach by evaluating the patient's body as a whole, finding the root cause of the problem and curing it.

Unlike other types of medicinal modalities, Functional Medicine is focused on digging deep into the biochemical and environmental history of the patient, rather than just providing treatment for the diagnosis.

  A Functional Medicine doctor devises a personalised treatment plan for every single patient depending on their detailed medical history.

This patient-specific medical care not only treats the underlying root cause of the disease but also helps identify & prevent any future additional health issues that may bound to occur.

  Integrative Medicine –

  Similar to Functional Medicine, Integrative Medicine is also a holistic medical domain which focuses on treating the whole person rather than just the disease.

The main focus of Integrative Medicine approach is to take into account every lifestyle routine of the patient including, mental, physical, nutritional and spiritual habits.

Depending on the lifestyle evaluation, an ideal alternative medical approach that best meets the patient's specific medical needs is chosen.

  Though both medicinal approaches seem similar, they have their own differences.

  Differences between Functional And Integrative Medicine:

  Functional medicine has devised protocols which involve the latest technologies available like peptide therapies. While integrative medicine is more focused on offering alternative modalities of treatment which are more traditional like ayurveda, chinese medicine.

Functional medicine helps to make individualised treatment plans, and can utilise your genetic tests to find which medicine or supplement will be best for you. Integrative medicine mostly relies on set treatment plans which are devised mainly through clinical experience of the doctor.

Functional medicine offers more advanced lab testing like checking for mold toxins, heavy metals, gut microbiome analysis etc. while integrative medicine relies mostly on traditional testing methods and clinical methods of diagnosis.

Functional medicine can help you identify the root cause of your problem by different tests, while integrative medicine offers you alternative methods of healing along with conventional medicine.

Both are great options and depending on your health needs, you can choose the best among these different alternative medical treatments.

  Want help choosing the best treatment approach for your health care needs?

    Set up a 15 min evaluation call with Dr. Gupta and get your questions cleared.

For More Info: functional medicine doctor online consultation

[naivelocus]

A simple high-throughput approach identifies actionable drug sensitivities in patient-derived tumor organoids

Establishment of 3D tumor models in ring format

To rapidly screen organoids, we first established a miniaturized system that allows the setup of hundreds of wells and perform assays with minimal manipulation. We adapted the geometry used to plate tumor cells in Matrigel, to generate mini-rings around the rim of the wells. This is attained by plating single-cell suspensions obtained from a cell line or a surgical specimen pre-mixed with cold Matrigel (3:4 ratio) in a ring shape around the rim in 96-well plates (Fig. 1a). Rings can be established using a single-well or multichannel pipette. Use of a robotic system or automated 96-well pipettor is theoretically feasible as long as temperature and plate positioning can be effectively controlled. The combination of small volume plated (10 µl) and surface tension holds the cells in place until the Matrigel solidifies upon incubation at 37 °C and prevents two-dimensional (2D) growth at the center of the wells. The ring configuration allows for media addition and removal so that changes of conditions or treatment addition to be easily performed by pipetting directly in the center of the well, preventing any disruption of the gel. Cancer cell lines grown in mini-ring format give rise to organized tumor organoids that recapitulate features of the original histology (Supplementary Fig. 1 and Supplementary Table 1).

Fig. 1

The mini-ring method for 3D tumor cell biology. a Schematics of the mini-ring setup. Cells are plated to form a solid thin ring as depicted in 1 and photographed in 2. The picture in 3 acquired with a cell imager shows tumor organoids growing at the periphery of the well as desired, with no invasion of the center. b Proliferation of primary tumor cells as measured by ATP release. Different seeding densities were tested and compared. This clinical sample grew and maintained the heterogeneity and histology of the original ovarian tumor, which had a high-grade serous carcinoma component (H&E left picture) and a clear cell component (H&E right picture). Scale bar, 20 µm. c Schematic of the drug-treatment experiments performed in the mini-ring setting. The pictures are representative images as acquired on different days using a Celigo cell imager. d–g Assays to monitor drug response of cell lines using the mini-ring configuration. Three drugs (ReACp53, Staurosporine, and Doxorubicin) were tested at five concentrations in triplicates for all cell lines. d ATP release assay (CellTiter-Glo 3D) readout. e,f Calcein/PI readout. e Representative image showing staining of MCF7 cells with the dyes and segmentation to quantify the different populations (live / dead). Scale bar, 400 nm. f Quantification of Calcein/PI assay for three-drug assay. g Quantification of cleaved caspase 3/7 assay. Doxorubicin was omitted due to its fluorescence overlapping with the caspase signal. For all graphs, symbols are individual replicates, bars represent the average, and error bars show SD

Similarly, we can routinely establish patient-derived tumor organoids (PDTOs) using the same geometry. As an example, Patient #1 was diagnosed with a high-grade mixed type carcinoma with both a high-grade serous component as well as a clear cell component (Supplementary Table 1 and Supplementary Fig. 2a). Cancer cells isolated from Patient #1 grown in our ring system show two distinct cytomorphologies: one group of cells have clear cytoplasm and cuboidal appearance, whereas the second group of cells organize in clusters in a columnar manner and have dense cytoplasm (Supplementary Fig. 2a). These morphologies are compatible with the two different histologies found in the original tumor, clear cell, and high-grade serous carcinoma (Supplementary Fig. 2a).

p53 is a defining marker of serous ovarian cancer, but is rarely expressed by clear cell ovarian tumors26. Both the tumor organoids and the primary cancer cells show similar p53 staining patters, with populations of p53-positive and p53-negative cells (Supplementary Fig. 2b,c). Thus, patient samples obtained at the time of surgery can proliferate in our system and maintain the heterogeneity of the original tumor as expected (Fig. 1b and Supplementary Fig. 2).

Assay optimization

Next we optimized treatment protocols and readouts for the mini-ring approach. Our standardized paradigm includes: seeding cells on day 0, establishing organoids for 2–3 days followed by two consecutive daily drug treatments, each performed by complete medium change (Fig. 1c). To demonstrate feasibility, we performed small-scale screenings testing three drugs at five different concentrations in triplicates, ReACp5317, Staurosporine27, and Doxorubicin (Fig. 1d–g, Supplementary Fig. 3–5). We optimized different readouts to adapt the method to specific research questions or instrument availability. After seeding cells in standard white plates, we performed a luminescence-based ATP assay to obtain a metabolic readout of cell status, calculate EC50, and identify cell-specific sensitivities (Fig. 1, Supplementary Figs. 3–4). Results show how the Matrigel in the mini-ring setup is thin enough to allow penetration not only of small molecules but also of higher molecular weight biologics such as peptides17. EC50s ranged between 2.5 µM (MDA-MB-468) and 10 µM (MCF7) for ReACp53, between 100 nM (MCF7) and 800 nM (PANC 03.27) for Staurosporine, and between 0.9 µM (SK-NEP) and 12 µM (MCF7) for Doxorubicin. Our measurements are in line with the Doxorubicin resistance of MCF7 cells grown in Matrigel in 3D that has been previously reported28.

We performed two consecutive treatments, which allows the drugs to not only penetrate the gel but also to reach organoids that may be bulky17. However, the assay is flexible and can be easily adapted to single treatments followed by longer incubations, multiple consecutive recurring treatments, multi-drug combinations, or other screening strategies (Supplementary Fig. 4).

We also implemented assays to quantify drug response by measuring cell viability after staining of live organoids with specific dyes followed by imaging. We optimized a calcein-release assay coupled to propidium iodide (PI) staining as well as a caspase 3/7 cleavage assay that can be readily performed after seeding the cells in standard black plates (Fig. 1e–g and Supplementary Fig. 5). For all assays, tumor organoids are stained following dispase release. After a 40 min incubation, organoids are imaged and pictures are segmented and quantified (Fig. 1e–g and Supplementary Fig. 5). All the assays are performed within the same well in which spheroids are seeded. Although the various assays we introduce are testing different aspects of cell viability and measure distinct biological events, results were mostly concordant across the methods for the three drugs tested (Fig. 1 and Supplementary Figs. 3 and 5).

Comparison of mini-ring method with traditional drop seeding

To confirm that 3D models established in mini-rings behave as those formed using traditional drop seeding methods, we directly compared the two techniques (Fig. 2). For this experiment, we seeded 5000 MCF7 cells/well either as drops or mini-rings and tested three drugs, ReACp53, Staurosporine, and Doxorubicin, in duplicates as described above. Results show that appearance of MCF7 3D spheroids (Fig. 2a) and drug sensitivities as measured by ATP assays (Fig. 2b) were undistinguishable when comparing mini-rings and drops. However, drops required individual manual aspiration and media addition, which resulted in longer processing times as no automation could be implemented.

Fig. 2

Comparison of different seeding procedures. a Bright-field images of rings and drops of MCF7 cells in Cultrex BME. Scale bar, 1 mm. b ATP assays showing identical sensitivities of mini-rings and drops to ReACp53, Staurosporine, and Doxorubicin tested at five concentrations in duplicates. Two independent experiments performed, all points shown. Bars represent the average, error bars show SD

Many other proteinaceous matrices are commercially available beside Matrigel. To confirm that other supports can be used for mini-rings, we used Cultrex BME in this experiment instead of Matrigel. Cells could be seeded as mini-rings and performance of Cultrex BME mirrored that of Matrigel (see Fig. 1d vs. Fig. 2b). In summary, different supports can be used to establish 3D models in mini-ring format and we observe no effect of mini-rings in terms of growth and drug treatment when comparing these with traditional seeding approaches.

Identification of actionable drug responses in PDTOs

A rapid functional assay to determine drug sensitivities of primary specimens can offer actionable information to help tailoring therapy to individual cancer patients3. We tested suitability of our approach to rapidly and effectively identify drug susceptibilities of three ovarian cancer samples and one high-grade serous peritoneal cancer specimen obtained from the operating room (Supplementary Table 1; Figs. 3 and 4). In all cases, ascites or tumor samples were processed and then plated as mini-rings (see Methods). To maximize the amount of information extracted from irreplaceable clinical samples, we investigated the possibility to concurrently perform multiple assays on the same plate. To do so, we first optimized the initial seeding cell number (5000 cells/well) to couple an ATP metabolic assay to 3D tumor count and total organoid area measurements. This seeding density yields a low-enough number of organoids to facilitate size distribution analysis but sufficient ATP signal to be within the dynamic range of the CaspaseGlo 3D assay. Careful consideration should be given as to whether the number of seeding cells can accurately recapitulate composition and heterogeneity of the tumor of origin. Cancer cell concentration can be reduced or augmented in our system depending on the characteristics of the tumor (Fig. 1b).

Fig. 3

Mini-ring approach to unveil drug response patterns in PDTOs. a Morphology of all PDTOs established in this study as visualized by bright-field microscopy. Morphology and 3D organization of the samples is highly variable. For instance, some of Patient #3 cells are arranged in fascicles within the Matrigel, likely representing the sarcomatous component of the tumor. Scale bar, 100 µm. b Results of kinase screening experiment for Patient #1 PDTOs. Three readouts were used for this assay: ATP quantification as measured by CellTiter-Glo 3D and organoid number or size quantification evaluated by bright-field imaging. Bright-field images were segmented and quantified using the Celigo S Imaging Cell Cytometer Software. Both organoid number and total area were evaluated for their ability to capture response to drugs. In this plot, each vertical line is one drug, all 240 tested are shown. Values are normalized to the respective vehicle controls for each method and expressed as %. AverageZ-score calculated as reported in Methods. c A representative image of the effects of the indicated drug treatments as visualized by the Celigo cell imager. Scale bar, 100 µm. d Small-scale kinase assay on Patient #1 primary PDTOs and PDX-derived cells. ATP readout. Four molecules not present in the primary screening were tested. Flavopiridol and BS-181 HCl are included as positive and negative control, respectively. t-test, **p < 0.01. e Comparison of the histology of the primary tumor with the established PDX. Scale bar: 100 µm

Fig. 4

Individualized response of PDTOs to tyrosine kinase inhibitors. a–c Results of kinase screening experiment on Patients #2–4 organoids. Each vertical line represents one of 241 tested drugs. Values are normalized to the respective vehicle controls (DMSO) for each method and expressed as %. d Expression of the multi-drug efflux protein ABCB1 in PDTOs as visualized by IHC. Patient #2 expresses very high levels of the ABC transporter. Scale bar: 60 µm. e Diagram illustrating limited overlap between the detected patterns of response identified through the mini-ring assay for all patients

For each patient sample, we seeded six 96-well plates and tested 240 protein kinase inhibitors FDA-approved or in clinical development. We tested each drug at two different concentrations (120 nM and 1 µM), for a total of 480 different conditions tested. Differently from established cancer cell lines, the number of cells obtained from surgical specimens can be limiting. As such, we opted for a two-dose focused screening, a common approach to identify potential hits. Validation can then be performed using frozen aliquots of cells that we cryopreserve after tissue processing post surgery (Supplementary Fig. 6b). However, our method can be adapted to accommodate any number of different screening designs, including concentration series (Fig. 1d–g and Supplementary Fig. 3 and 5) or multiple drug combinatorial assays.

For PDTOs, we used the same experimental paradigm optimized using cell lines (Fig. 1c). All steps (media change, drug treatment) were automated and performed in < 2 min/plate using a Beckman Coulter Biomek FX integrated into a Thermo Spinnaker robotic system. At the end of each experiment, PDTOs are first imaged in bright-field mode for organoid count/size distribution analysis followed by an ATP assay performed on the same plates. The measurements yielded high-quality data that converged on several hits, highlighting the feasibility of our approach to identify potential leads (Figs. 3 and 4).

Patient #1: high-grade mixed type carcinoma

Cells obtained from Patient #1 at the time of cytoreductive surgery were chemo-naive and the heterogeneous nature of this clear cell/high-grade serous tumor was recapitulated in the PDTOs (Table 1, Fig. 1b, and Supplementary Fig. 2). Despite aggressive debulking surgery and treatment with carboplatin and paclitaxel regimens, Patient #1 had persistent disease, never achieved complete remission, and overall survival from diagnosis was 11 months. Resistance to carboplatin was also observed in our high-throughput assay, with no significant reduction of viability observed at either 10 or 25 µM concentrations (Supplementary Fig. 6a). The organoids were however sensitive to ~6% of the protein kinase inhibitors tested (16/240), with sensitivity defined as residual cell viability ≤ 25% and average Z-score ≤ − 5 (Table 1, Supplementary Table 2, Supplementary Fig. 7a; see Methods for Z-score calculations). Patient #1’s tumor organoids responded to 58% of all cyclin-dependent kinase (CDK) inhibitors tested (7/12 total, 11 different compounds, and one, Flavopiridol, in two formulations). In particular, cells appeared highly sensitive to inhibitors hitting CDK1/2 in combination with CDK4/6 or CDK5/9 (Table 1, Fig. 3c, and Supplementary Table 3). Interestingly, CDK inhibitors have found limited applicability in ovarian cancer therapy so far29. Based on the profiles of the CDK inhibitors tested and on the response observed (Supplementary Table 3), we selected four untested molecules to assay. We anticipated that Patient #1 would not respond to Palbociclib (targeting CDK4/6) and THZ1 (CDK7), while expecting a response to JNJ-7706621 (CDK1/2/3/4/6) and AZD54338 (CDK1/2/9; Supplementary Table 3). BS-181 HCl and Flavopiridol were included as negative and positive control, respectively. Results show that organoids were not sensitive to JNJ-7706621 but had a strong response to THZ1 (Fig. 3d). Both THZ1 and BS-181 HCl specifically target CDK7. Nevertheless, Patient #1 PDTOs showed a strong response to the former but no response to the latter, which could be attributed to the different activity of the two as recently observed in breast cancer30. We detected elevated CDK7 protein expression in Patient #1 PDTOs (Supplementary Fig. 7b).

Table 1 List of molecules causing over 75% reduction in viability in PDTOs established from Patient #1’s tumor

We also attempted to validate the screening results in vivo by establishing PDXs injecting Patient #1 cells subcutaneously in NSG mice (500 K/mouse, 12 mice). However, only three mice developed PDXs over the course of 5 months. The xenografts resembled the histology of the primary tumor (Fig. 3e). To test whether the PDXs had a similar response to CDK inhibitors, we dissociated the PDX to single-cell suspension and generated organoids from one of them (Fig. 3a, d, e). The PDX-derived organoids showed an overall trend toward a reduction in sensitivity to CDKs when compared with the PDTOs. We observed a statistically significant decrease in response to 0.1 µM THZ1, and 1 µM JNJ-7706621 and AZD5438 (p < 0.01, Fig. 3d) in the PDX-derived organoid compared with the PDTOs. This is not unexpected, as human cancer cells grown in mice rapidly diverge from the tumor they were obtained from31,32.

Patient #2: platinum-resistant high-grade serous ovarian carcinoma

Patient #2 was diagnosed with progressive, platinum-resistant high-grade serous ovarian cancer and was heavily pretreated before sample procurement (Supplementary Table 1). Patient #2 PDTOs were also platinum-resistant in our system (Supplementary Fig. 6a), with no reduction of viability observed upon treating the cells with either 10 or 25 µM carboplatin. The PDTOs showed a strong response (residual cell viability ≤ 25% and average Z-score ≤ − 5) to only 0.8% of all drugs tested (2/240, Fig. 4a, Table 2, and Supplementary Fig. 7a). We validated the results by performing a dose–response study (Supplementary Fig. 6b). We exposed patient #2 organoids to eight concentrations of the two hits identified in the screening, BGT226 and Degrasyn (0, 0.05, 0.1, 0.25, 0.5, 1, 5, and 10 µM), in duplicates. We used the same experimental setup as indicated above and the EC50s calculated using the ATP results from two independent experiments confirm Patient #2’s organoid sensitivity to low concentrations of the two drugs (Supplementary Fig. 6b).

Table 2 Drug leads causing over 75% cell death in PDTOs from Patient #2, #3, and #4

Patient #2 PDTOs showed only a moderate response to our positive control, Staurosporine, a pan-kinase inhibitor with very broad activity27. The lack of response to multiple therapies observed for Patient #2 led us to hypothesize that there could be overexpression of efflux membrane proteins. Indeed, the PDTOs showed a high level of expression of ABCB1 (Fig. 4d). High expression of the ATP-dependent detox protein ABCB1 is frequently found in chemoresistant ovarian cancer cells and recurrent ovarian cancer patients’ samples, and has been correlated with poor prognosis33,34.

We found a moderate response, comparable to the effect of Staurosporine (~40% residual cell viability), to EGFR/HER2 inhibitors including Lapatinib and WZ8040 (Table 2). We could detect high expression of EGFR at the plasma membrane of the tumor cells (Supplementary Fig. 7c), as is common for platinum-resistant ovarian cancer35.

Patients #3: carcinosarcoma of the ovary

Patient #3 presented with a carcinosarcoma of the ovary, an extremely rare and aggressive ovarian tumor, which has not been fully characterized at the molecular level yet36,37 (Supplementary Table 1, Fig. 4b, Table 2, and Supplementary Fig. 7a). In our screening, the PDTOs established from this tumor responded to ~3% of all tested kinase inhibitors (7/240, residual cell viability ≤ 25%, and average Z-score ≤ − 1.5), including CDK inhibitors and phosphatidyl inositol 3-kinase (PI3K) inhibitors.

Patient #4: high-grade peritoneal carcinoma

Patient #4 was diagnosed with a high-grade peritoneal tumor and showed a response to only 0.8% of all tested drugs (2/240, Supplementary Table 1, Fig. 4c, Table 3, and Supplementary Fig. 7a and 7d). The PDTOs showed a marked response to two drugs, one pan-Akt inhibitor (GSK690693) and a PI3K/mammalian target of rapamycin (mTOR) inhibitor (BGT226), with measured cell viability ≤ 25% and average Z-score ≤ − 5. However, different from Patient #2, Patient #4 PDTOs were sensitive to Staurosporine, with only 9 ± 1% residual viability after 2 days of treatment. Protein kinase C, which is the primary target of Staurosporine, is also a secondary target of GSK69069338.

Although only 2 inhibitors caused a 75% reduction in cell viability, 11 agents caused ≥ 50% cell death (Z-score ≤ − 5). Using this cutoff, we could identify six mTOR inhibitors including Omipalisib, Apitolisib, and Sapanisertib. These constitute 30% of all the mTOR inhibitors tested, pinpointing a potential vulnerability of this pathway.

— Communications Biology - nature.com science feeds