Current Cancer Reports

A Knowledge-Based Planning model for IMRT in breast and lung cancer

K. Keshav Kumar — 2024-10-29

Objective: The advent of Knowledge-Based Planning (KBP) models has introduced a transformative approach to Intensity-Modulated Radiation Therapy (IMRT) treatment planning in breast cancer and lung cancer cases. This paper explores the application of KBP models to these specific cancer types, highlighting their potential to enhance treatment accuracy, efficiency, and patient outcomes.
Methods: By leveraging historical treatment data and machine learning techniques, KBP-IMRT offers a data-driven framework for optimizing dose distributions, minimizing radiation exposure to healthy tissues, and improving overall treatment plan quality.
Results: Through a comprehensive review of the literature and clinical case studies, this paper underscores the advantages of KBP-IMRT, such as streamlined planning processes and improved plan consistency, while acknowledging the challenges associated with model development and implementation.
Conclusion: As the field of radiotherapy continues to evolve, KBP models hold the promise of shaping the future of personalized and precise cancer treatment strategies.

Opportunities and challenges of multidisciplinary conversion therapy in advanced hepatocellular carcinoma

Ju-Hang Chu — 2024-09-11

Surgical resection is still the most important radical treatment for primary hepatocellular carcinoma (HCC), but at present, the resection rate of newly diagnosed patients with HCC is only 30%. The recurrence rate of newly diagnosed patients suitable for surgical resection within 5 years after surgery is as high as 40%~70%. Low initial resection rate and high postoperative recurrence rate are important reasons restricting the overall treatment effects of HCC in China. Under this background, effectively improving the resection rate of HCC and reducing the postoperative recurrence rate have become the key topics to improve the treatment effects of HCC. Some initially unresectable HCC patients may have access to surgery through conversion therapy. Conversion therapy, which mainly involves the combination of local, systemic, and multiple treatment strategies, offers hope for patients with advanced HCC. But there are still some patients who do not benefit from conversion therapy. So, how to improve the conversion success rate is still one of the challenges that clinicians need to solve.

Deep learning based capsule networks for breast cancer classification using ultrasound images

Stephen Afrifa — 2024-08-27

Purposes: Breast cancer (BC) is a disease in which the breast cells multiply uncontrolled. Breast cancer is one of the most often diagnosed malignancies in women worldwide. Early identification of breast cancer is critical for limiting the impact on affected people's health conditions. The influence of technology and artificial intelligence approaches (AI) in the health industry is tremendous as technology advances. Deep learning (DL) techniques are used in this study to classify breast lumps.
Materials and Methods: The study makes use of two distinct breast ultrasound images (BUSI) with binary and multiclass classification. To assist the models in understanding the data, the datasets are exposed to numerous preprocessing and hyperparameter approaches. With data imbalance being a key difficulty in health analysis, due to the likelihood of not having a condition exceeding that of having the disease, this study applies a cutoff stage to impact the decision threshold in the datasets data augmentation procedures. The capsule neural network (CapsNet), Gabor capsule network (GCN), and convolutional neural network (CNN) are the DL models used to train the various datasets.
Results: The findings showed that the CapsNet earned the maximum accuracy value of 93.62% while training the multiclass data, while the GCN achieved the highest model accuracy of 97.08% when training the binary data. The models were also evaluated using a variety of performance assessment parameters, which yielded consistent results across all datasets.
Conclusion: The study provides a non-invasive approach to detect breast cancer; and enables stakeholders, medical practitioners, and health research enthusiasts a fresh view into the analysis of breast cancer detection with DL techniques to make educated judgements.

Nanotherapeutics to cure inflammation-induced cancer

Rajiv Kumar — 2024-07-02

Aims: Nanotherapeutics are being explored as a potential solution to treat inflammation-induced cancer. Nanotherapeutics enhance innate immune cells' immunity, enabling them to fight tumors effectively. These cells secrete specific chemicals like cytokines, allowing them to replicate quickly and respond to future threats, making them suitable for immunotherapy.
Methods: Nanotechnology can significantly improve human health by enhancing infection detection, prevention, and treatment. Nanomedicines, composed of restorative and imaging compounds in submicrometer-sized materials, aim to deliver effective treatments and limit inflammation in healthy body areas. Combining nanotechnology and clinical sciences, nanoparticles are suitable for gene therapy and have been developed for treating various diseases, including cancer, cardiovascular, diabetes, pulmonary, and inflammatory diseases.
Results: Neutrophils and their offspring, including films and extracellular vehicles, are crucial drug transporters for enhanced growth therapy. Tumor microenvironment inputs can modify tumor-associated neutrophils (TANs), which are essential for tumor growth and healing. Human tumor intratumor heterogeneity is crucial for tumor growth and healing. Nanomedicines have shown potential in targeted delivery, toxicity reduction, and therapeutic effectiveness enhancement. However, clinical relevance and efficacy remain inadequate due to a lack of understanding of the interaction between nanomaterials, nanomedicine, and biology. The diverse biological milieu impacts the dynamic bioidentity of nanoformulations, and their interactions can modify therapeutic function or cellular absorption.
Conclusion: Nanotechnology holds great promise for improving human health by detecting, preventing, and treating infections. Nanomedicines, a fusion of clinical sciences and nanotechnology, use submicrometer-sized transporter materials for therapy delivery and reducing contamination. Nanoparticles' small size and high surface-to-volume ratio can benefit gene therapy. Research has led to a wide range of nanomedicine products globally.

Breast carcinoma in the Democratic Republic of the Congo: Characterization of hormone receptors

Guy Ilunga Nday — 2024-03-26

Purpose: Breast cancer is a heterogeneous disease, and understanding its characteristics is crucial for effective treatment. Therefore, this study aims to investigate breast carcinomas as a function of hormone receptors (estrogen and progesterone) in the Democratic Republic of the Congo (DRC), which can contribute to better management of breast cancer cases in the country.
Methods: We conducted an analytical cross-sectional study from 2014 to 2016 in the cities of Kinshasa and Lubumbashi. Using non-random sampling, we collected 86 cases of breast carcinoma.
Results: The study found that out of the 86 cases of breast carcinoma, 33 patients (38.3%) had both types of hormone receptors (ER+/PgR+), while 37 patients (43.0%) had negative results for both receptor types (ER-/PgR-). Additionally, 15 patients (17.4%) had only estrogen receptors. The study did not find any significant association between the presence of estrogen receptors and patient age, T stage, histological type, and Ki67 proliferation index. However, the study did observe that estrogen receptors were significantly more present in grade I and II tumors (74.4%) than in grade III tumors (40.4%) (Odds ratio=4.3 [1.7-10.8]; p=0.003).
Conclusion: The findings of this study demonstrate a high prevalence of hormone receptors in breast cancer cases in the DRC. Additionally, the study revealed a significant association between the presence of estrogen receptors and tumor grade, underlining the relevance of these markers in the characterization and treatment of the disease.

Perspectives on chemotherapy-induced toxicities in pancreatic cancer

Henu Kumar Verma — 2024-02-20

Despite breakthroughs in screening, identification, and therapy, pancreatic cancer (PC) remains a serious issue in cancer-related mortality. This comprehensive review investigates the long-term and latent effects of chemotherapy in PC, focusing on commonly used medicines such as gemcitabine, docetaxel, irinotecan, nab-paclitaxel, and others. Gemcitabine, a common PC medication, causes a variety of adverse effects, including myelosuppression and weariness. Combination therapy, such as docetaxel and irinotecan, enhance toxicity, resulting in problems such as neutropenia and gastrointestinal difficulties. Significantly, chemotherapy-related complications, such as thrombosis and cardiac difficulties connected to paclitaxel, present serious concerns. Erlotinib, gefitinib, vatalanib, and sunitinib studies show significant side effects. Despite ongoing challenges, determining the causes of the low objective response rate in gemcitabine-refractory patients remains challenging. The study emphasizes the importance of future advances in cancer etiology, arguing for large, straightforward studies examining combination chemotherapies to improve tolerance and minimize chemotherapy-induced sequelae. This overview serves as a thorough guide for physicians, researchers, and policymakers as they navigate the complex terrain of PC chemotherapy, providing significant insights to improve patient care.

Risk of severe immune-related adverse events in cancer patients with pre-existing autoimmunity receiving immune checkpoint inhibitor therapy

Dayna Jill Isaacs — 2024-01-29

Purpose: To evaluate the frequency and severity of irAEs in patients with pre-existing autoimmunity, including irAE-related morbidity and mortality, irAE-related management and resolution, and outcome of ICI rechallenge, to better understand the treatment options for this vulnerablepatient population.
Methods: We designed a retrospective, single-center, case-control study at a large, academic medical center to evaluate the incidence and severity of irAEs in patients with pre-existing autoimmunity compared to controls. Controls were matched 2:1 for age, sex, cancer histology, and ICI class. Patients were identified with ICD 9 and 10 codes followed by manual chart extraction. Cases were defined as patients with pre-existing, systemic autoimmunity. The primary outcome was severe irAE (Grade 3 or higher by Common Terminology Criteria for Adverse Events) within 6 months of ICI therapy. Secondary outcomes included response to ICIs, resolution of the irAE, ICI rechallenge success, and survival. Statistical analyses were performed by Chi-square, Fishers exact, Mann-Whitney, and Log-rank tests.
Results: Of 3,130 patients treated with ICIs from 2015-2021, 28 cases with pre-existing autoimmune disease were identified and were matched with 56 controls. Pre-existing autoimmune conditions included antiphospholipid syndrome, inflammatory polyarthritis, juvenile rheumatoid arthritis, multiple sclerosis, psoriatic arthritis, rheumatoid arthritis, and type I diabetes. Multiple cancer histologies, including genitourinary, gynecologic, head & neck, hepatobiliary, lung, melanoma, and pancreatic, were represented. Six of 28 cases (21.4%) experienced severe irAEs compared to 9/56 (16.1%) controls; the odds of developing a severe irAE were not significantly different (OR 0.43, 95% CI 0.083-2.33, p = 0.627, ns). Moreover, there were no significant differences in overall survival or tumor response between the two groups. The majority of irAEs resolved without long-term sequelae (66.7% of cases, 55.6% of controls). The majority of patients who were rechallenged with ICIs were successful in continuing therapy (66.7% of cases, 100% of controls).
Conclusion: Our study suggests that patients with pre-existing autoimmune disease can be treated with ICI cancer therapies and experience rates of severe irAEs and overall survival that are similar to those of the general population. These data can aid oncologists in discussing risks and benefits of ICIs when treating patients with pre-existing autoimmunity and solid tumors.

Tumor microenvironment

Ping Wang — 2023-06-08

Retrospection and prospect of Current Cancer Reports (CCR)

Ying-Yu Cui — 2023-04-13

Black-White disparities in fatigue and comorbidity among breast cancer survivors

Steven S. Coughlin — 2023-02-09