Chemotherapy For Treatment Of Cancer Research Articles

Model based smooth super-twisting control of cancer chemotherapy treatment

Chemotherapy is one of the most efficient methods for treating cancer patients. Chemotherapy aims to eliminate cancer cells as thoroughly as possible. Delivering medications to patients’ bodies through various methods, either oral or intravenous is part of the chemotherapy process. Different cell-kill hypotheses take into account the interactions of the expansion of the tumor volume, external drugs, and the rate of their eradication. For the control of drug usage and tumor volume, a model based smooth super-twisting control (MBSSTC) is proposed in this paper. Firstly, three nonlinear cell-kill mathematical models are considered in this work, including the log-kill, Norton-Simon, and Emax hypotheses subject to parametric uncertainties and exogenous perturbations. In accordance with clinical recommendations, the tumor volume follows a predefined trajectory after chemotherapy. Secondly, the MBSSTC is applied for the three cell-kill models to attain accurate trajectory tracking even in the presence of uncertainties and disturbances. Compared to conventional super-twisting control (STC), the non-smooth term is introduced in the proposed control to enhance the anti-disturbance capability. Finally, simulation comparisons are performed across the proposed MBSSTC, conventional STC, and proportional–integral (PI) control methods to show the effectiveness and merits of our designed control method.

Prospective Single-Arm Feasibility of Supervised Virtual Exercise in Women Living with Ovarian Cancer: The BE-BALANCED Study

Background: Access to exercise programming that addresses the unique needs of women living with and beyond ovarian cancer is limited. Feasible and accessible supportive care programs to enhance physical function and quality of life are needed. We aimed to assess the feasibility of a 12-week virtually delivered exercise program for women living with and beyond ovarian cancer. Methods: BE-BALANCED was a prospective single-arm feasibility pilot study. Women who had completed primary chemotherapy treatment of ovarian cancer within the past year were recruited through oncologist referrals or self-referral. The 12-week group exercise program targeting aerobic capacity, functional strength, balance, and range of motion was conducted virtually twice weekly using Zoom. Feasibility measures were accrual, attendance, adherence, and attrition. Physical function was evaluated using the Short Physical Performance Battery and selected components of the Senior Fitness Test. Results: Fourteen participants enrolled in the study (47% of the accrual target). Feasibility goals for the exercise sessions were met for attendance (84% ± 19%), adherence to virtual sessions (78% ± 19%), and fidelity of group belonging (18% ± 4%), and met for overall attrition (21%). Improvements were observed in gait speed, 30-second bicep curls, 6-minute walk, chair stand, and emotional well-being (P < .05). Participant satisfaction with the program was high (4.4/5). Conclusion: Our findings demonstrated the feasibility of a virtually delivered exercise program for women living with and beyond ovarian cancer, with favorable attendance, adherence, and safety data. The program showed potential in improving physical outcomes and quality of life for participants. However, recruitment was a challenge. Future interventions could consider different approaches to increase recruitment.

Attitudes of physicians and patients toward immediate and intraoperative chemotherapy treatment in colon cancer

IntroductionWe have shown in a Phase I trial that immediate adjuvant chemotherapy (IAC) during surgical resection and immediately postoperative is safe and feasible in patients with colon cancer (CC). IAC avoids delays in adjuvant treatment and has the potential to improve survival and quality of life. We aim to determine patients and providers attitudes toward this novel multidisciplinary treatment approach. MethodsTwo web-based surveys were administered to newly diagnosed CC patients, survivors, surgeons and oncologists. Surveys assessed treatment preferences and perceived barriers to IAC. Chi-square tests were conducted to compare differences between patients’ and providers’ responses. ResultsResponses were collected from 35 patients and 40 providers. Patients were more willing to: (1) proceed with IAC to finish treatment earlier thus possibly improving quality of life (p = 0.001); (2) proceed with IAC despite potential side effects (p < 0.001); and (3) proceed with a dose of intraoperative chemotherapy even if on final pathology, may not have been needed (p = 0.002). Patients were more likely to indicate no barriers to collaborative care (p = 0.001) while providers were more likely to cite that it is time consuming, thus a barrier to participation (p = 0.001), has scheduling challenges (p = 0.001), and physicians are not available to participate (p = 0.003). ConclusionsWe observed a discordance between what providers and patients value in perioperative and adjuvant CC treatment. Patients are willing to accept IAC despite potential side effects and without survival benefit, highlighting the importance of understanding patient preference.

Abstract B105: Evaluating the racial equity of a digital health patient-reported symptom management system in patients receiving chemotherapy

Abstract INTRODUCTION. The development of behavioral &amp; supportive care interventions to improve quality of life for people receiving chemotherapy treatment for cancer, even with demonstrated overall efficacy, may unintentionally result in unequal benefit including across racial subgroups. The purpose of this study was to determine if Symptom Care at Home (SCH), is efficacious, digital health patient-reported outcome (PROs) symptom managment system, provide equitable benefit across racial subgroups. METHODS. A randomized trial was conducted to determine the active components of SCH. Participants reported daily on 11 common treatment symptoms through an Interactive Voice Response (IVR) telephone-based system that transmitted data through telephone lines. Continuous measures &amp; standard deviations with ordinal &amp; categorical measures, frequencies &amp; percentages of the totals were summarized. Comparisons between participants across Georgia &amp; Utah &amp; between Black &amp; White race were completed using Students t-test &amp; chi-square tests. Statistical analyses were completed using a 5% level of significance. This analysis compared these two groups to determine if participation with the SCH digital health tool &amp; symptom reduction benefits were equitable. RESULTS. Participants were 239 Black plus 13 Other or mixrd-race patients (251; 86%) as compared with the 118 White patients (32%) receiving chemotherapy treatment in Atlanta, Georgia. Blacks had slightly lower call compliance 67.59% (25.92%) versus (vs) Utah Whites 72.75% (22.45%) p=0.005; lower days in study Blacks 48.9% (29.9%) vs 80.8% (50.3%), p&amp;lt;0.001; &amp; lower completion of study all 3 cycles of chemotherapy &amp; still calling (65.4% vs 75.2%), p&amp;lt;0.001. Georgians also had significantly lower average total alerts 5.08% (10.69%) vs Utah 8.12% (15.20%), p&amp;lt;0.001 and lower presence of at least one moderate/severe symptom for most of the 11 symptoms. Georgians were more likely to be Female (72.2% vs 49.2%, p&amp;lt;0.001); Non-marreid (37.7% vs 72.9%, p&amp;lt;0.001); Non-degree holder (59.9% vs 39.8%, p&amp;lt;0.001); &amp; have diagnosis of Breast Cancer (34.9% vs 12.7%). Blacks had slightly lower call complaince 65.17% (27.1%) vs Whites 72.75% (22.45%), p=0.005; but with no statistically significant difference in number of days in study 49.0% (30.2%) vs 48.6% (29.5%), p=0.911; no statistically significant difference in completion of all 3 cycles of chemotherapy (65.4% vs 63.5%, p=0.895); with difference in average number of total alerts 4.89% (10.93%) vs 5.48% (10.20%, p=0.621). CONCLUSIONS. This study found no racial diffrences in how participants engaged the SCH digital health platform or lenght of study, although the Black plus other raccial group reported daily symptoms 7.5% less days than the White grpup. The degree of benefit found from the SCH was equitably distributed across racial categories. Carefully designed digital health tools utilized to measure &amp; manage PROs in patients receiving chemotherapy can achieve equitable symptom benefit across racial groups &amp; may contribute to reducing racial diparities in cancer symptom care. Citation Format: Mary Gullatte, Eli Iacob, Gary Donaldson, Kathi Mooney. Evaluating the racial equity of a digital health patient-reported symptom management system in patients receiving chemotherapy [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr B105.

Measuring Drug Response with Single-Cell Growth Rate Quantification.

Intratumoral heterogeneity is a substantial cause of drug resistance development during chemotherapy or other drug treatments for cancer. Therefore, monitoring and measuring cell exposure and response to drugs at the single-cell level are crucial. Previous research suggested that the single-cell growth rate can be used to investigate drug-cell interactions. However, currently established methods for quantifying single-cell growth are limited to isolated or monolayer cells. Here, we introduce a technique that accurately measures both 2D and 3D cell growth rates using label-free ratiometric stimulated Raman scattering (SRS) microscopy. We use deuterated amino acids, leucine, isoleucine, and valine, as tracers and measure the C-D SRS signal from deuterium-labeled proteins and the C-H SRS signal from unlabeled proteins simultaneously to determine the cell growth rate at the single-cell level. The technique offers single-cell level drug sensitivity measurement with a shorter turnaround time (within 12 h) than most traditional assays. The submicrometer resolution of the imaging technique allows us to examine the effects of chemotherapeutic drugs, including kinase inhibitors, mitotic inhibitors, and topoisomerase II inhibitors, on both the cell growth rate and morphology. The capability of quantifying 3D cell growth rates provides insight into a deeper understanding of the cell-drug interaction in the actual tumor environment.

Impaired microvascular reactivity in patients treated with 5-fluorouracil chemotherapy regimens: Potential role of endothelial dysfunction

Background5-fluorouracil (5-FU) is the second most common cancer chemotherapy associated with short- and long-term cardiotoxicity. Although the mechanisms mediating these toxicities are not well understood, patients often present with symptoms suggestive of microvascular dysfunction. We tested the hypotheses that patients undergoing cancer treatment with 5-FU based chemotherapy regimens would present with impaired microvascular reactivity and that these findings would be substantiated by decrements in endothelial nitric oxide synthase (eNOS) gene expression in 5-FU treated human coronary artery endothelial cells (HCAEC). MethodsWe first performed a cross-sectional analysis of 30 patients undergoing 5-FU based chemotherapy treatment for cancer (5-FU) and 32 controls (CON) matched for age, sex, body mass index, and prior health history (excluding cancer). Cutaneous microvascular reactivity was evaluated by laser Doppler flowmetry in response to endothelium-dependent (local skin heating; acetylcholine iontophoresis, ACh) and -independent (sodium nitroprusside iontophoresis, SNP) stimuli. In vitro experiments in HCAEC were completed to assess the effects of 5-FU on eNOS gene expression. Results5-FU presented with diminished microvascular reactivity following eNOS-dependent local heating compared to CON (P = 0.001). Iontophoresis of the eNOS inhibitor L-NAME failed to alter the heating response in 5-FU (P = 0.95), despite significant reductions in CON (P = 0.03). These findings were corroborated by lower eNOS gene expression in 5-FU treated HCAEC (P < 0.01) compared to control. Peak vasodilation to ACh (P = 0.58) nor SNP (P = 0.39) were different between groups. ConclusionsThe present findings suggest diminished microvascular function along the eNOS-NO vasodilatory pathway in patients with cancer undergoing treatment with 5-FU-based chemotherapy regimens and thus, may provide insight into the underlying mechanisms of 5-FU cardiotoxicity.

Deep reinforcement learning-based control of chemo-drug dose in cancer treatment

Background and objectiveAdvancement in the treatment of cancer, as a leading cause of death worldwide, has promoted several research activities in various related fields. The development of effective treatment regimens with optimal drug dose administration using a mathematical modeling framework has received extensive research attention during the last decades. However, most of the control techniques presented for cancer chemotherapy are mainly model-based approaches. The available model-free techniques based on Reinforcement Learning (RL), commonly discretize the problem states and variables, which other than demanding expert supervision, cannot model the real-world conditions accurately. The more recent Deep Reinforcement Learning (DRL) methods, which enable modeling the problem in its original continuous space, are rarely applied in cancer chemotherapy. MethodsIn this paper, we propose an effective and robust DRL-based, model-free method for the closed-loop control of cancer chemotherapy drug dosing. A nonlinear pharmacological cancer model is used for simulating the patient and capturing the cancer dynamics. In contrast to previous work, the state variables and control action are modeled in their original infinite spaces to avoid expert-guided discretization and provide a more realistic solution. The DRL network is trained to automatically adjust the drug dose based on the monitored states of the patient. The proposed method provides an adaptive control technique to respond to the special conditions and diagnosis measurements of different categories of patients. Results and conclusionsThe performance of the proposed DRL-based controller is evaluated by numerical analysis of different diverse simulated patients. Comparison to the state-of-the-art RL-based method, which uses discretized state and action spaces, shows the superiority of the approach in the process and duration of cancer chemotherapy treatment. In the majority of the studied cases, the proposed model decreases the medication period and the total amount of administrated drug, while increasing the rate of reduction in tumor cells.

Clinical Impact of Nutrition and Inflammation Assessment Tools in Pancreatic Cancer Treatment.

Perioperative adjuvant treatment and complete resection is the standard treatment for resectable pancreatic cancer and systemic chemotherapy is standard treatment for unresectable pancreatic cancer. To improve the survival of patients with pancreatic cancer, it is necessary to identify promising biomarkers to optimize the treatment. The availability of biomarkers may allow patients to receive a more aggressive or less toxic treatment. Recent studies showed that the inflammatory and nutritional status perioperatively and/or during chemotherapy affect short and long-term oncological outcomes in pancreatic cancer. Introduction of inflammatory and nutritional status evaluation in pancreatic cancer treatment might improve the postoperative surgical complications or chemotherapy-induced adverse events. However, to introduce these various nutritional and inflammation assessment tools in daily clinical practice, it is necessary to understand the characteristics of each nutrition and inflammation assessment tool. This review summarizes the background, current status, and future perspectives of nutrition and inflammation assessment tools in pancreatic cancer treatment.

Retracted: Construction of Nursing Practice Model in Case Management of Concurrent Chemotherapy and Radiochemotherapy Treatment in Cervical Cancer.

[This retracts the article DOI: 10.1155/2022/5450575.].

Preparation, Characterization and Cytotoxic Studies of Cisplatin-containing Nanoliposomes on Breast Cancer Cell Lines

Objective: Today, cancer is one the most important challenges in modern medicine. Breast carcinoma is one type of cancer that is treated with cisplatin, a chemotherapy drug. By using liposomal nanocarriers, this study seeks to increase the therapeutic efficiency of cisplatin. Method: The zeta potential, particle size, and drug-release characteristics of nanoliposomal cisplatin were evaluated after it had been synthesized using the reverse phase evaporation technique. The cytotoxicity rate of nanoliposomal cisplatin was then assessed using the T-47D breast cancer cell line. Results: This study’s liposomal nanoparticles (NPs) had a zeta potential of -24.9 mV and a particle size of 342.3 nm. 3.51% and 79.6%, respectively, were found to be the drug loading level and amount of encapsulated drug. A significant improvement over the free drug was seen in this nanoliposome’s cytotoxic effect on the T-47D breast cancer cell line (P&lt;0.05). Conclusion: According to what we have discovered, cisplatin liposomal nanocarriers may prove to be a cutting-edge chemotherapy treatment for breast cancer.

Multi-Walled Carbon Nanotube Array Modified Electrode with 3D Sensing Interface as Electrochemical DNA Biosensor for Multidrug-Resistant Gene Detection.

Drug resistance in cancer is associated with overexpression of the multidrug resistance (MDR1) gene, leading to the failure of cancer chemotherapy treatment. Therefore, the establishment of an effective method for the detection of the MDR1 gene is extremely crucial in cancer clinical therapy. Here, we report a novel DNA biosensor based on an aligned multi-walled carbon nanotube (MWCNT) array modified electrode with 3D nanostructure for the determination of the MDR1 gene. The microstructure of the modified electrode was observed by an atomic force microscope (AFM), which demonstrated that the electrode interface was arranged in orderly needle-shaped protrusion arrays. The electrochemical properties of the biosensor were characterized by cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). Chronocoulometry (CC) was used for the quantitative detection of the MDR1 gene. Taking advantage of the good conductivity and large electrode area of the MWCNT arrays, this electrochemical DNA sensor achieved a dynamic range from 1.0 × 10-12 M to 1.0 × 10-8 M with a minimal detection limit of 6.4 × 10-13 M. In addition, this proposed DNA biosensor exhibited high sensitivity, selectivity, and stability, which may be useful for the trace analysis of the MDR1 gene in complex samples.

Optimizing the enzymatic release of MMAE from isoDGR-based small molecule drug conjugate by incorporation of a GPLG-PABC enzymatically cleavable linker.

Antibody-Drug Conjugates (ADCs) and Small Molecule-Drug Conjugates (SMDCs) represent successful examples of targeted drug-delivery technologies for overcoming unwanted side effects of conventional chemotherapy in cancer treatment. In both strategies, a cytotoxic payload is connected to the tumor homing moiety through a linker that releases the drug inside or in proximity of the tumor cell, and that represents a key component for the final therapeutic effect of the conjugate. Here, we show that the replacement of the Val-Ala-p-aminobenzyloxycarbamate linker with the Gly-Pro-Leu-Gly-p-aminobenzyloxycarbamate (GPLG-PABC) sequence as enzymatically cleavable linker in the SMDC bearing the cyclo[DKP-isoDGR] αVβ3 integrin ligand as tumor homing moiety and the monomethyl auristatin E (MMAE) as cytotoxic payload led to a 4-fold more potent anti-tumoral effect of the final conjugate on different cancer cell lines. In addition, the synthesized conjugate resulted to be significantly more potent than the free MMAE when tested following the "kiss-and-run" protocol, and the relative potency were clearly consistent with the expression of the αVβ3 integrin receptor in the considered cancer cell lines. In vitro enzymatic cleavage tests showed that the GPLG-PABC linker is cleaved by lysosomal enzymes, and that the released drug is observable already after 15min of incubation. Although additional data are needed to fully characterize the releasing capacity of GPLG-PABC linker, our findings are of therapeutic significance since we are introducing an alternative to other well-established enzymatically sensitive peptide sequences that might be used in the future for generating more efficient and less toxic drug delivery systems.

Predicting Chemotherapy Benefit across Different Races in Early-Stage Breast Cancer Patients Using the Oncotype DX Score.

Oncotype DX assay, a multigene molecular test, has been widely used to stratify relapse risk and guide chemotherapy treatment in breast cancer. However, the optimal threshold of the Oncotype DX score in predicting chemotherapy benefit and its racial variation has not been investigated. In this study, we apply a random forest survival model to the SEER-Oncotype cohort data (Surveillance, Epidemiology, and End Results with Oncotype DX test information for breast cancer patients) and determine chemotherapy benefit thresholds in early-stage, estrogen-receptor-positive (ER+), and HER2-negative (HER2-) patients of different races. Our results indicate that early-stage ER+, HER2-, and LN-/LN+ patients may benefit from receiving chemotherapy at a lower Oncotype DX score than current guidelines (Recurrence Score, RS > 25 or RS > 30) suggest. According to the estimated chemotherapy sensitivity thresholds from our models, 2.05-2.72-fold more lymph-node-negative (LN-) and 2.08-5.02-fold more lymph-node-positive (LN+) patients who may not currently be recommended for chemotherapy by their Oncotype DX test result may actually have the potential to benefit from chemotherapy. Furthermore, our models indicate a racial difference in chemotherapy benefit: white, black, and Asian women with early-stage ER+/LN- tumors benefit from chemotherapy when their Oncotype DX scores are greater than 19.9, 37.2, and 18.0, respectively. Our study provides a method for calibrating multigene molecular tests to help guide treatment decisions in racially and ethnically diverse patients with cancer. Specifically, we identify key chemotherapy sensitivity thresholds for the Oncotype DX recurrence score test in breast cancer patients and provide evidence that certain patients may benefit from receiving chemotherapy at a lower threshold than the current clinical guidelines suggest.

Paradigm shift of chemotherapy and systemic treatment for biliary tract cancer.

Biliary tract cancers (BTC) are frequently identified at late stages and have a poor prognosis due to limited systemic treatment regimens. For more than a decade, the combination of gemcitabine and cis-platin has served as the first-line standard treatment. There are few choices for second-line chemo-therapy. Targeted treatment with fibroblast growth factor receptor 2 inhibitors, neurotrophic tyrosine receptor kinase inhibitors, and isocitrate dehydrogenase 1 inhibitors has had important results. Immune checkpoint inhibitors (ICI) such as pembrolizumab are only used in first-line treatment for microsatellite instability high patients. The TOPAZ-1 trial's outcome is encouraging, and there are several trials underway that might soon put targeted treatment and ICI combos into first-line options. Newer targets and agents for existing goals are being studied, which may represent a paradigm shift in BTC management. Due to a scarcity of targetable mutations and the higher toxicity profile of the current medications, the new category of drugs may occupy a significant role in BTC therapies.

Molecular characterization of resistance to immune checkpoint inhibitor and chemotherapy treatment in advanced non-small cell lung cancer.

9034 Background: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and a leading cause of cancer death. Standard of care (SOC) treatment for advanced NSCLC patients include immune checkpoint inhibitors (ICI) and/or chemotherapy (CT). However, the majority of patients do not respond to SOC therapy. Mechanisms of resistance and how they differ across treatments are not fully understood. We characterized molecular markers of resistance for advanced NSCLC patients with ICI monotherapy, CT, or combination ICI-CT. Methods: Advanced stage III or IV NSCLC patients with adenocarcinoma histology who received at least 21 days of ICI monotherapy, CT, or combination ICI-CT were identified from a de-identified, multimodal real-world database from Tempus Labs, Inc. All patients had a tissue biopsy taken within 100 days prior to the specified therapy start and all samples underwent next generation sequencing with the Tempus xT assays (DNA-seq of 596-648 genes at 500x coverage and whole transcriptome RNA-seq). Resistance to therapy was defined as having time to next treatment &lt; 90 days, or disease progression or death within 120 days of therapy initiation. We characterized the clinical and molecular characteristics of patients and compared differential expression of genes by resistance status for each cohort. Results: A total of 365 patients were included in the study (ICI = 121, CT = 122, ICI-CT = 122). Across cohorts, 30% of patients were identified as having resistance to treatment (ICI = 35%, CT = 23%, ICI-CT = 32%). 53% of patients were &gt; 65 years (median [range] = 67 [25- 88]), and 53% were males. Most patients were white (63%) and had a history of tobacco use (85% current or former smoker). At the time of biopsy, most patients were diagnosed with metastatic NSCLC (Stage IV = 73%) and had received no previous lines of therapy (92%). The alteration frequencies of known NSCLC oncogenic driver mutations including TP53 (65%), KRAS (42%), STK11 (14%), KEAP1 (11%), and EGFR (9%) were broadly consistent with previous characterizations of NSCLC. Validated biomarkers of response to ICI treatment such as Tumor Mutation Burden, IFN-γ signaling, PD-1, and PD-L1 expression were negatively associated with resistance to ICI treatment. Across the ICI, ICI-CT, and CT cohorts, 253, 153, and 178 genes, respectively, were significantly upregulated (FDR &lt; 0.05, LogFC &gt; 1) in patients with resistance to treatment. Of the 550 distinct genes correlated to resistance across treatments, 95% were unique to each cohort, and only 32 genes (5%) were shared across more than one treatment cohort. Conclusions: Distinct molecular characteristics were associated with resistance to ICI and/or CT treatment. This suggests that mechanisms of resistance to ICI monotherapy, ICI-CT, or CT could be separate and unique. Further research can provide valuable insights for novel therapies or combinations.

CNN-based deep learning method for predicting the disease response to the Neoadjuvant Chemotherapy (NAC) treatment in breast cancer

ObjectiveThe objective of the study is to evaluate the performance of CNN-based proposed models for predicting patients' response to NAC treatment and the disease development process in the pathological area. The study aims to determine the main criteria that affect the model's success during training, such as the number of convolutional layers, dataset quality and depended variable. MethodThe study uses pathological data frequently used in the healthcare industry to evaluate the proposed CNN-based models. The researchers analyze the classification performances of the models and evaluate their success during training. ResultsThe study shows that using deep learning methods, particularly CNN models, can offer strong feature representation and lead to accurate predictions of patients' response to NAC treatment and the disease development process in the pathological area. A model that predicts ‘miller coefficient’, ‘tumor lymph node value’, ‘complete response in both tumor and axilla’ values with high accuracy, which is considered to be effective in achieving complete response to treatment, has been created. Estimation performance metrics have been obtained as 87%, 77% and 91%, respectively. ConclusionThe study concludes that interpreting pathological test results with deep learning methods is an effective way of determining the correct diagnosis and treatment method, as well as the prognosis follow-up of the patient. It provides clinicians with a solution to a large extent, particularly in the case of large, heterogeneous datasets that can be challenging to manage with traditional methods. The study suggests that using machine learning and deep learning methods can significantly improve the performance of interpreting and managing healthcare data.

Multiscale modeling of the dynamic growth of cancerous tumors under the influence of chemotherapy drugs

A comprehensive model of chemotherapy treatment of cancer can help us to optimize the drug administration/dosage and improve the treatment outcome. In the present study, a multiscale mathematical model of tumor growth during chemotherapy treatment is developed to predict its response to the medication and cancer progression. The modeling is a continuous multiscale simulation consisting of three tissue phases including cancer cells, normal cells, and extracellular matrix. In addition to the drug administration, the impacts of immune cells, programmed cell death, nutrient competition, and glucose concentration are included. The outputs of our mathematical model conform to the published experimental and clinical data, and it can be used in optimizing chemotherapy, and personalized cancer treatment.

Effects of Adriamycin-Cytoxan chemotherapy on hematological and electrolyte parameters among breast cancer patients.

Adriamycin-Cytoxan (AC) is a common chemotherapy treatment for breast cancer (BC) patients. Its electrolyte and hematological adverse effects have not been addressed adequately. This study aimed to assess the effect of AC on hematological and electrolyte parameters among BC patients. A hospital-based comparative cross-sectional study design was conducted from March to November 2022. Randomly selected AC-treated (n=100) and untreated (n=100) patients were included. Structured questionnaire and medical records were used to collect sociodemographic data. Anthropometric parameters, hematological indices, and serum electrolytes were measured. Cobas Integra 400+and SYSMEX-XT-4000i were used to analyze serum electrolytes and hematological indices respectively. The data were analyzed using SPSS version 25. Independent t-test and chi-square test were used. p-value <0.05 was considered statistically significant. AC-treated patients' mean total white blood cell (TWBC), neutrophil (NE), lymphocyte (LY), red blood cell (RBC), hemoglobin (Hgb), hematocrit (HCT), and sodium(Na+) values were significantly reduced (p<0.05) than patients with no treatment. However, mean eosinophils (EO), platelet (PLT) counts, red cell distribution-width (RDW), potassium (K+), and plateletcrit (PCT values were significantly increased (p<0.05). The majority of blood cells and serum sodium were affected by AC treatment. Incorporating these parameters in the routine analysis and further studies on the detailed mechanism of action of this drug is required.

Canine appendicular osteosarcoma: Amputation and chemotherapy in cancer treatment

Osteosarcoma is a malignant bone neoplasm with a high incidence in adult and giant breed dogs, with the appendicular skeleton being the most affected compared to the axial one. The symptoms usually present are claudication, swelling and may or may not be associated with episodes of fractures. The diagnosis consists of imaging exams, and in many cases, confirmation is only possible through bone biopsy. Due to aggressiveness the prognosis is unfavorable, and the best treatment for this case is limb amputation, with the intention of removing the primary tumor. The dog, in this report, was diagnosed by bone biopsy, whose histopathological result was osteoblastic osteosarcoma. The tumor originated in the distal femur of the left pelvic limb and the patient was referred for amputation, the surgical technique used was coxofemoral disarticulation. As an adjuvant treatment, chemotherapy with carboplatin was instituted. There were fivw sessions in an interval of 21 in 21 days, without reaction or alterations in the complementary exams. Pulmonary macro metastases were not identified in the radiographic examination, and a disease-free interval was observed, guaranteeing quality of life for the patient, despite being a very aggressive tumor.

Identification of rare variants involved in the risk of second cancer following radiotherapy and chemotherapy treatment of pediatric cancers

Identification of rare variants involved in the risk of second cancer following radiotherapy and chemotherapy treatment of pediatric cancers